Digital watermarking and data hiding with narrow-band absorption materials

ABSTRACT

The present disclosure relates to signal processing such as image processing, signal encoding, digital watermarking and data hiding. A sparse or dense digital watermark signal can be conveyed with a narrow-band absorption material corresponding to a center wavelength of a Point of Sale (POS) barcode scanner. The POS barcode scanner typically captures 2D imagery. Since the narrow-band absorption material absorbs over a narrow-band it is relatively imperceptible to the Human Visual System (HVS) but can be seen by the POS scanner.

RELATED APPLICATION DATA

This application is a continuation of U.S. application Ser. No.16/422,597, filed May 24, 2019 (U.S. Pat. No. 11,062,418), which is adivision of U.S. application Ser. No. 15/669,103, filed Aug. 4, 2017(U.S. Pat. No. 10,304,151), which is a division of U.S. application Ser.No. 15/073,483, filed Mar. 17, 2016 (U.S. Pat. No. 9,754,341), whichclaims the benefit of US Provisional Patent Application Nos. 62/263,369,filed Dec. 4, 2015, 62/255,181, filed Nov. 13, 2015, 62/208,493, filedAug. 21, 2015, 62/202,723, filed Aug. 7, 2015, 62/142,399, filed Apr. 2,2015, and 62/136,146, filed Mar. 20, 2015. Each of these patentdocuments is hereby incorporated herein by reference in its entirety.

This application is also related to U.S. patent application Ser. No.15/072,884, filed Mar. 17, 2016, and published as US 2017-0024840 A1,which is hereby incorporated herein by reference in its entirety.

TECHNICAL FIELD

The invention relates to signal communication including digitalwatermarking and machine-readable indicia and, in particular, toconveying such signals in noisy environments. In some implementations, adigital watermark signal in carried on a substrate with

BACKGROUND AND SUMMARY

Many approaches have been developed for encoding machine readableinformation on objects. Perhaps the most well-known technique is theubiquitous barcode. Over the years, various barcode types have beencreated, which differ significantly from the name-sake pattern of darklinear bars on a lighter background. Now, the term barcode has been usedto encompass machine symbols in various shapes, sizes, patterns andcolors.

These types of codes were primarily developed to be reliable datacarriers that could be applied with a wide array of print and markingtechniques on many types of objects. They were not designed, in mostcases, to be aesthetically pleasing, or to be weaved into other imagery,whether it be graphical designs, text etc. on product packaging, labels,or displays. As such, in most applications, these codes occupy adedicated location on an object, where no other information is located.This approach has worked well to reliably apply identifying informationto objects, including packaging, parts (“Direct Part Marking”), etc.Nevertheless, placing the code at a dedicated location limits theability to find and read the code. When used on consumer goods, it isoften located on the back or bottom of the item so as not to interferewith consumer messaging and product aesthetics. This placement of thecode tends to slow down code reading or increase scanner cost byrequiring additional components to capture multiple views of an object.It also increases risk of injury due to the need for workers tore-position the object to scan the code for auto-identification.Obviously, this undermines the theoretical speed and reliabilityadvantages of auto-identification.

Data signaling techniques have been developed that have promise inaddressing these drawbacks while providing additional advantages. Onesuch technique is referred to as digital watermarking. Digitalwatermarking provides a method of encoding information within imagecontent or object surface topology. As such, it can be applied over someor all of the surface of an object with minimal cost and changes toworkflow, addressing the drawbacks of barcodes while being fullycompatible with them. Additionally, the digital watermarking applies tomany different types of media, including analog and digital forms ofimages (including video) and audio. This enables enterprises toimplement auto-identification and auxiliary data encoding across all oftheir assets, including physical and digital media. Some (but not all)embodiments of digital watermarking include hiding the presence of thesignal.

Digital watermarking often carries information. This information isoften referred to as the “watermark payload” or “watermark message,” avariable sequence of message symbols inserted per unit of host content.The watermark message can carry variable information. In one example,the watermark message carries information corresponding to a so-calledGlobal Trade Item Number (GTIN). A GTIN is an identifier for trade itemsdeveloped by GS1. Such identifiers are used to look up productinformation in a database (often by entering the number through a barcode scanner pointed at an actual product) which may belong to aretailer, manufacturer, collector, researcher, or other entity.

There are, of course, limits to the extent to which a watermark payloadcan be inserted in existing image or audio (the host signal) withoutimpacting the perceptual quality of the host. Generally speaking, hostsignals with more variable information provide greater opportunity toinsert the payload, whereas host signals with uniform or solid tonesprovide less opportunity for insertion of the payload. In cases wherethere is little host signal content, it may not be possible to encodethe payload, or if it is encoded, it is done so with a greater impact onperceptual quality.

Perceptual quality relates to the extent to which a human perceives achange in an image. This is a challenging metric, as it has asignificant subjective component. Nevertheless, the human visual systemhas been modeled, and data from user tests can be used to construct aclassifier that measures in a quantitative way, whether a change to animage or video will be visible or deemed objectionable. Human visualsystem models and classifiers based on them provide a measure of whethera change made to an image is likely to be visible, and also, canquantify visibility in units such as Just Noticeable Difference (JND)units. For applications where images are modified to insert a datasignal, the perceptual quality is a constraint on data signal design andencoding strategy. The importance of this constraint on signal designand encoding methodology varies with the application. The flexibility ofthe watermark signal allows it to be transformed into visual elements ofthe object's design in various ways, and as such, provides many optionsfor adapting the signal to satisfy perceptual quality constraints fordifferent types of images and applications.

Literature documenting our earlier work describes various ways to dealwith host signal types that lack signal content compatible with dataencoding. We refer to one approach as “sparse” marking as the datacarrying signal is formed as a sparse array of signal elements. Forvisual media, the sparse array of elements works well on portions of ahost image that are uniform or solid tones or appear largely blank. Withgreater sophistication in the signaling, it also is effective inencoding blank areas around text of a document, label, visual display orpackage, as our signaling schemes employ robust data encoding strategiesto mitigate impact of interference from the text. In one embodiment, asparse mark is comprised of a pattern of spatial locations where ink isdeposited or not. For example, the sparse signal may be comprised of inkdots on a light background, such that the signal forms a pattern ofsubtly darker spatial locations. The signal is designed to be sparse bythe spacing apart of the darker locations on the light background.Conversely, the signal may be designed as an array of lighter “holes” ona relatively darker background. See, for example, U.S. Pat. Nos.6,345,104, 6,993,152 and 7,340,076, which are hereby incorporated byreference in their entirety.

As described in U.S. Pat. No. 6,345,104, this strategy of formingpatterns of light and dark elements is consistent with our earlierdigital watermarking strategies that modulate luminance. For example, alighter element encodes a first message symbol (e.g., binary one), whilea darker element encodes a second symbol (e.g., binary zero).

The sparse signal has minimal impact on visual quality due to its sparsearrangement. However, the trade-off for applications like automaticobject identification is that more sophistication is required in thedata signaling methodology to ensure that the data carried within thesparse signal may be reliably and efficiently recovered in manydifferent and challenging environments. The sparse nature of the signaldictates that less payload may be encoded per unit of object surfacearea. Further, within the sparse signal, there is a trade-off betweenallocating signal for payload capacity versus signal for robustness. Inthe latter category of robustness, the signaling scheme must supportrecovery in environments of geometric distortion, which occurs when thesparse signal is imaged from various angles, perspectives and distances,in the presence of noise of various types that tends to interfere withthe data signal.

There are various sources of geometric distortion that need to beaddressed to reliably recover the payload in the sparse signal. Examplesof geometric distortion include signal cropping and warping. Croppingtruncates portions of the sparse signal, e.g., in cases where only aportion is captured due to occlusion by other objects or incompletecapture by a scanner. Warping occurs when the surface on which thesparse signal is applied is curved (on cups or cans) or wrinkled (onbags and flexible plastic or foil pouches) and when the sparse signal isimaged from a surface at various perspectives.

The design of a signaling scheme must also account for practicalchallenges posed by constraints on digital circuitry, processors andmemory for encoding and decoding. These include computationalefficiency, power consumption, memory consumption, memory bandwidth, useof network bandwidth, cost of hardware circuitry or programmableprocessors/circuitry, cost of designing and integrating encoders anddecoders within signal transmitter and receiver, equipment, etc. Forexample, some encoding schemes may provide optimized encoding ordecoding, but may not be applicable because they are too slow forencoding or decoding in real time, e.g., as the host signal is beingtransmitted, received, updated, or being processed with multiple othersignal processing operations concurrently.

The design must also account for practical challenges of the markingtechnology. The printing technology must be able to reproduce the signalreliably. This includes transformation of the data signal in the RasterImage Processor as well as application of an image to an object.

The design must also account for practical challenges posed by 2D imagecapture and associated optics. Scanners at Point of Sale (POS), forexample, tend to be tuned to detect black and white barcodes (e.g., witha spectral range that focuses on image capture around image content at awavelength at or around 660 nm), and as such, the illumination type andsensors may have a much more limited range of spectral bands andresolutions that the device can sense, e.g., in the range of 630-710 nm.When we use the term “at or around 660 nm,” we mean a wavelength withinthe range of 640-680 nm. In one particular example, a red illuminationscanner includes a wavelength in the range of 650-670 nm, and may becentered or include a peak in this range, e.g., at 660 nm. In anotherexample, a red illumination scanner includes a wavelength in the rangeof 650-710 nm, which we refer to as “at or around 690 nm”. Otherscanners may be centered or include a peak, e.g., at 688-690 nm.

Sparse signaling is particularly challenging in that the sparse natureof the signal provides less opportunity to include signal for payloadand robustness. In particular, there is less opportunity to includepayload and synchronization. The strategy for synchronization may relyon an explicit synchronization component or an implicit synchronizationcomponent. In the latter case, the encoding of the payload may bearranged in a manner that provides a pattern that facilitates detectionand synchronization.

Another important consideration for some applications is compatibilityand inter-operability with other messaging protocols. For example, inthe case of applying identification over the surface of objects, thesignal encoding and decoding strategy should preferably support variousprotocols to deal with various image types, printing technologies, andscanner technologies. This design consideration dictates that sparsesignaling should be compatible with encoding and decoding othersignaling, like legacy encoding schemes on older objects and densewatermark signaling strategies and barcodes of various types.Preferably, the installed base of decoder technology should be able toefficiently decode signals from various signaling types, including newsparse signal arrangements.

One aspect of the disclosure is a method for inserting a sparse,variable data carrying signal into an image. This method provides afirst signal component, which facilitates a synchronization function ofthe sparse signal. It also provides a second signal component that ismodulated to carry a variable data signal. The first and second signalcomponents have values located at coordinates within a two-dimensionalblock. The method combines the first signal component and the secondsignal component to produce the sparse, variable data carrying signal bysetting sparse elements at coordinates within the two-dimensional blockwhere the first and second component signal values provide compatiblemodulation of the image. The method inserts the sparse, variable datacarrying signal into at least a first image layer or channel of an imagedesign.

In this method, the sparse signal elements are set at coordinates wherethe signal components provide compatible modulation. Compatiblemodulation is where the signals of the two components comply withconsistency rule. For example, the signals have a consistent directionof modulation of an optical property at a coordinate within thetwo-dimensional block. One optical property is brightness or lightnessand it may be modulated in a darker or lighter direction. Other examplesof optical properties are chrominance and hue. Components that modulatean image in the same direction, namely both darker or both lighter, havea compatible modulation direction.

The consistency rule may also be determined by consistency in amount ofmodulation. For instance, modulation of the components is compatible ifthe value of signal components fall within a common range bounded by atleast one threshold. In some cases, components are multi-valued, andthen quantized to quantization levels or bins (multi-dimensional valuesfalling in a bin space are quantized to a bin). This may be implementedby applying a threshold, in which values within a range are set to aparticular value. Multi-valued components are converted into binarylevels (e.g., 1 or 0) or more than two levels (e.g., 1, 0, −1), forexample. The consistency rule is evaluated on the output of this processby comparing the values of the signal components at a coordinate andsetting sparse element or not at the coordinate based on theconsistency. A logical AND operation or like comparison may be used todetermine whether the signal components satisfy the consistency rule,e.g., quantize to a common quantization level or range bounded by athreshold.

The quantizing of a signal can be used to determine a distribution ofsparse elements in a block. In one embodiment, for example, a signalcomponent (e.g., sync component) is quantized to provide a sparsedistribution within a block. The sparse signal is then formed based onwhere the signal components comply with a consistency rule. Theconsistency rule evaluates signal components at these locations and setsa sparse element at the coordinate where they are consistent.

One target-rich environment for applying a sparse mark (also referred toas a “sparse watermark” or “sparse digital watermark”) is consumerpackaged goods (e.g., boxes of cereal, yogurt packages, cans of soup,etc.). However, some packaging materials and printing processes presentchallenges. For example, so-called dry offset printing (discussed below)does not accommodate overprinting. Flexography printing creates otherproblems in keeping tight printing tolerances. Other challenges includewatermarking light (or dark) printed areas under the spectralconstraints of most POS scanners (e.g., red LED scanners).

We address some of these problems by conveying a digital watermark(e.g., a sparse or dense mark) with narrow-band absorption (and other)materials. Such materials can be combined with a coating such as avarnish, laminate, ink extender, clear primer, adhesive, sealant orother coating. The coating can be provided over tricky color areaswithout adversely affecting the aesthetics of a consumer packaged gooddesign.

Another aspect of this disclosure is a printed package for a retailproduct comprising a substrate. The substrate includes a first area anda second area, in which the first area and the second area compriseadjacent non-overlapping areas. The first area comprises a first offsetink or flexography ink printed thereon. The printed package comprises acoating, the coating comprising a narrow-band absorption material with aspectral absorbance peak in the range of 630 nm-710 nm. The coating isselectively applied over portions of both the first area and the secondarea in a 2D pattern representing an encoded digital watermark signal,the 2D pattern being redundantly applied on the printed package. Theprinted package comprises more area within the first area and the secondarea without the coating than area with the coating. The one or moreinstances of the 2D pattern are detectable from machine-analysis ofillumination of the printed package, the illumination have anillumination peak in the range of 630 nm-710 nm.

A related aspect of the disclosure is a system comprising the abovepackage, a point of sale scanner comprising an LED with an illuminationpeak in the range of 630 nm-710 nm, and a digital watermark detector foranalyzing 2D imagery captured by the point of sale scanner to recoverthe encoded digital watermark signal.

Yet another aspect of the disclosure is a printed package for a retailproduct prepared by a process comprising: providing a sparse pattern ofelements at coordinates within a two-dimensional block, providing asignal component, the signal component being modulated to carry avariable data signal, and generating a sparse, variable data carryingsignal by distributing the signal component within a two-dimensionalblock based on the location of the sparse pattern of elements; applyinga first ink on a surface of the printed package, the surface comprisinga first area and a second area, the first ink applied only in the firstarea; applying a coating over portions of both the first area and thesecond area according to a pattern representing the two-dimensionalblock, the coating comprising a narrow-band absorption material with aspectral absorption having an absorbance peak in the range of 630 nm-710nm, the two-dimensional block being redundantly applied on the printedpackage, in which the printed package comprises more area within thefirst and second areas without the coating than area with the coating,in which one or more instances of the two-dimensional block aredetectable from machine-analysis of illumination of the printed package,the illumination have an illumination peak in the range of 630 nm-710nm.

Another aspect of this disclosure provides a method comprising: scanninga printed object with a red illumination scanner, the red illuminationscanner having a wavelength at or around 660 nm, said scanning yieldingscan data, wherein the printed object includes a coating printed thereonthrough an offset printing press, the coating including a narrow-bandabsorption additive that absorbs at or around 660 nm, the coatingprinted in a manner to convey an encoded plural-bit message, the encodedplural-bit message corresponding to a GTIN number; analyzing the scandata with one or more programmed processors to decode the encoded pluralbit message, said analyzing yielding the GTIN number; and providing theGTIN number as an output.

Yet another aspect of the disclosure provides a method of offsettingcolor casting for a printed object. The method includes: providing afirst additive that absorbs light energy at or around a center frequencyof an illumination source; providing a second additive that absorbs inthe ultra-violet spectrum, yet fluoresces at or around the centerfrequency of the illumination source, wherein a combination of spectralresponses of the first additive and the second additive offset colorcasting; printing the first additive, second additive and a color on theprinted object, wherein the printing conveys an encoded plural bitsignal.

In this document, we detail various signaling schemes, including schemesfor generating signals, and encoding and decoding them in various objecttypes and object marking technologies. We describe schemes that encode asparse signal within host signal carrier in a manner that is robust,flexible to achieve perceptual quality constraints, and providesimproved data capacity. We also describe use of narrow-band absorptionmaterials which may correspond with a central wavelength and width of anarrow-band LED (or laser) illumination, e.g., from a Point of Sale(POS) scanner.

BRIEF DESCRIPTION OF THE DRAWINGS

The patent or application file contains at least one drawing executed incolor. Copies of this patent or patent application publication withcolor drawing(s) will be provided by the Office upon request and paymentof the necessary fee.

FIG. 1 is a block diagram of a signal encoder for encoding a data signalinto a host signal.

FIG. 2 is a block diagram of a signal decoder for extracting a datasignal from a host signal.

FIG. 3 is a flow diagram illustrating operations of a signal generator.

FIG. 4 is a diagram illustrating an example of a sparse signalgenerator.

FIG. 5 is a diagram illustrating a refinement of a sparse signalgenerator like the one in FIG. 4.

FIG. 6 is a histogram of a digital watermark signal component.

FIG. 7 is a histogram of another digital watermark signal component.

FIG. 8 is a histogram of a combination of the digital watermark signalcomponents of FIGS. 6 and 7, and also depicts examples of differentthresholds used to generate a binary image comprising black and whitepixels from an image comprised of multi-valued pixels.

FIG. 9 is a diagram illustrating another refinement of the sparse signalgenerator of FIG. 4.

FIG. 10 is a diagram illustrating application of a threshold to awatermark signal, and the resulting output for three differentthresholds.

FIG. 11 illustrates a portion of a sparse signal.

FIG. 12 illustrates the sparse signal of FIG. 11, modified to reduce thesignal using a line screen approach.

FIG. 13 is a diagram illustrating a method of decoding a watermarksignal or sparse signal.

FIG. 14 illustrates one class of pattern detection methods in which atemplate (labeled “signal”) and the filtered spectrum of a suspectsignal (labeled “measured”) are transformed into a log polar (LP)coordinate system and correlated with each other to produce a LPcorrelation.

FIG. 15 is a diagram depicting properties of additives used to enhancedetection of encoded data signals.

FIG. 16 illustrates an electronic device in which encoding and decodingmay be implemented.

FIG. 17A is a diagram showing reflectance (absorption) relative towavelength.

FIG. 17B shows various colors and their grayscale representation(“scanner sees”) as seen by a POS scanner with a red LED illumination ator around 660 nm.

FIG. 17C show an absorbance response curve for a narrow-band absorptionmaterial.

FIG. 18 is a diagram showing an offsetting fluorescence at a particularabsorption wavelength.

FIG. 19 is a timing chart for a phosphorescence relative to signaldetection.

FIG. 20 is a diagram illustrating a machine-readable code redundantlyprinted on a packaged good.

FIG. 21 is a diagram showing excitation and emission spectrum for anadditive.

FIG. 22 is a diagram showing reflectance (absorption) relative towavelength.

FIG. 23 is a diagram showing a material with a step-function forabsorption, which remains high into the Infrared region.

DETAILED DESCRIPTION Signal Encoder and Decoder

FIG. 1 is a block diagram of a signal encoder for encoding a sparsesignal. FIG. 2 is a block diagram of a compatible signal decoder forextracting a payload from a sparse signal encoded on an object or withinan image displayed on a video display.

Encoding and decoding is typically applied digitally, yet the signal isexpected to survive digital to analog transformation and analog todigital transformation. For example, the encoder generates an imageincluding the sparse signal that is converted to a rendered form, suchas a printed image, displayed image or video. We use the term “printing”to encompass a wide variety of marking technologies, includingengraving, etching, stamping, etc. as there are a variety of ways toimpart the image carrying the sparse signal to an object. Prior todecoding, a receiving device captures an image or stream of images ofthe object through its image sensor such as a camera (e.g., CMOS orCCD), and converts it to an electronic signal, which is digitized andprocessed by signal decoding modules.

Inputs to the signal encoder include a host signal 150 and auxiliarydata 152. The objectives of the encoder include encoding a robust signalwith desired capacity per unit of host signal, while maintainingperceptual quality within a perceptual quality constraint. In somecases, there may be very little variability or presence of a hostsignal, in which case, there is little host interference, on the onehand, yet little host content in which to mask the presence of the datachannel visually. Some examples include a region of a package designthat is devoid of much image variability (e.g., a single, uniformcolor), the surface of a part, a label or receipt, or video displaywithout natural imagery (e.g., just simple graphics, uniform or solidtones and text).

The auxiliary data 152 includes the variable data information (e.g.,payload) to be conveyed in the data channel, possibly along with otherprotocol data used to facilitate the communication.

The protocol defines the manner in which the signal is structured andencoded for robustness, perceptual quality or data capacity. For anygiven application, there may be a single protocol, or more than oneprotocol. Examples of multiple protocols include cases where there aredifferent versions of the channel, different channel types (e.g.,several sparse signal layers within a host). An example is a packagedesign or document, in which rich imagery are encoded with densewatermark signal protocols, and blank or uniform or solid tone areas areencoded with tints or sparse signal protocols. Different protocolversions may employ different robustness encoding techniques ordifferent data capacity. Protocol selector module 154 determines theprotocol to be used by the encoder for generating a data signal. It maybe programmed to employ a particular protocol depending on the inputvariables, such as user control, application specific parameters, orderivation based on analysis of the host signal.

Perceptual analyzer module 156 analyzes the input host signal todetermine parameters for controlling signal generation and embedding, asappropriate. It is not necessary in certain applications, while inothers it may be used to select a protocol and/or modify signalgeneration and embedding operations. For example, when encoding in hostcolor images that will be printed or displayed, the perceptual analyzer156 may be used to ascertain color content and masking capability of thehost image.

The sparse mark may be included in one of the layers or channels of theimage file, e.g., corresponding to:

-   -   a color channel of the image, e.g., Red Green Blue (RGB);    -   components of a color model (Lab, HSV, HSL, etc.);    -   inks of the printer (Cyan, Magenta, Yellow, or Black (CMYK)), a        spot color layer (e.g., corresponding to a Pantone color), which        are specified to be used to print the image;    -   a coating (e.g., varnish, UV layer, lacquer, sealant, extender,        primer, etc.);    -   other material layer (metallic substance, e.g., metallic ink or        stamped foil where the sparse signal is formed by stamping holes        in the foil or removing foil to leave sparse dots of foil); etc.

The above are typically specified in a design file, and are manipulatedby our encoder. For example, our encoder is implemented as softwaremodules of a plug-in to Adobe Photoshop image processing software.Design files in this software are specified in terms of image layers orimage channels. The encoder may modify existing layers, channels orinsert new ones. A plug-in can be utilized with other image processingsoftware, e.g., Adobe Illustrator.

The perceptual analysis performed in the encoder depends on a variety offactors, including color or colors of the sparse signal, resolution ofthe sparse signal, dot structure and screen angle used to print imagelayer(s) with sparse signal, content within the layer of the sparsesignal, content within layers under and over the sparse signal, etc. Theperceptual analysis may lead to the selection of a color or combinationof colors in which to encode the sparse signal that minimizes visualdifferences due to inserting the sparse signal in an ink layer or layerswithin the image. This selection may vary per embedding location of eachsparse signal element. Likewise, the amount of signal at each locationmay also vary to control visual quality. The encoder can, depending onthe associated print technology in which it is employed, vary sparsesignal by controlling parameters such as:

-   -   dot shape,    -   signal amplitude at a dot,    -   ink quantity at a dot (e.g., dilute the ink concentration to        reduce percentage of ink),    -   structure and arrangement of dot cluster or “bump” shape at a        location of a sparse signal element or region of elements. An        arrangement of ink applied to x by y two dimensional array of        neighboring locations can be used to form a “bump” of varying        shape or signal amplitude, as explained further below.

The ability to control printed dot size and shape is a particularlychallenging issue and varies with print technology. Dot size can varydue to an effect referred to as dot gain. The ability of a printer toreliably reproduce dots below a particular size is also a constraint.

The sparse signal may also be adapted according to a blend model whichindicates the effects of blending the ink of the sparse signal layerwith other layers and the substrate.

In some cases, a designer may specify that the sparse signal be insertedinto a particular layer. In other cases, the encoder may select thelayer or layers in which it is encoded to achieve desired robustness andvisibility (visual quality of the image in which it is inserted).

The output of this analysis, along with the rendering method (display orprinting device) and rendered output form (e.g., ink and substrate) maybe used to specify encoding channels (e.g., one or more color channels),perceptual models, and signal protocols to be used with those channels.Please see, e.g., our work on visibility and color models used inperceptual analysis in our U.S. application Ser. No. 14/616,686 (nowU.S. Pat. No. 9,380,186), Ser. No. 14/588,636 (now U.S. Pat. No.9,401,001) and Ser. No. 13/975,919 (now U.S. Pat. No. 9,449,357), PatentApplication Publication 20100150434, and U.S. Pat. No. 7,352,878, whichare each hereby incorporated by reference in its entirety.

The signal generator module 158 operates on the auxiliary data andgenerates a data signal according to the protocol. It may also employinformation derived from the host signal, such as that provided byperceptual analyzer module 156, to generate the signal. For example, theselection of data code signal and pattern, the modulation function, andthe amount of signal to apply at a given embedding location may beadapted depending on the perceptual analysis, and in particular on theperceptual model and perceptual mask that it generates. Please see belowand the incorporated patent documents for additional aspects of thisprocess.

Embedder module 160 takes the data signal and modulates it onto achannel by combining it with the host signal. The operation of combiningmay be an entirely digital signal processing operation, such as wherethe data signal modulates the host signal digitally, may be a mixeddigital and analog process or may be purely an analog process (e.g.,where rendered output images are combined). As noted, a sparse signalmay occupy a separate layer or channel of the design file. This layer orchannel may get combined into an image in the Raster Image Processor(RIP) prior to printing or may be combined as the layer is printed underor over other image layers on a substrate.

There are a variety of different functions for combining the data andhost in digital operations. One approach is to adjust the host signalvalue as a function of the corresponding data signal value at anembedding location, which is controlled according to the perceptualmodel and a robustness model for that embedding location. The adjustmentmay alter the host channel by adding a scaled data signal or multiplyinga host value by a scale factor dictated by the data signal valuecorresponding to the embedding location, with weights or thresholds seton the amount of the adjustment according to perceptual model,robustness model, available dynamic range, and available adjustments toelemental ink structures (e.g., controlling halftone dot structuresgenerated by the RIP). The adjustment may also be altering by setting orquantizing the value of a pixel to particular sparse signal elementvalue.

As detailed further below, the signal generator produces a data signalwith data elements that are mapped to embedding locations in the datachannel. These data elements are modulated onto the channel at theembedding locations. Again please see the documents incorporated hereinfor more information on variations.

The operation of combining a sparse signal with other imagery mayinclude one or more iterations of adjustments to optimize the modulatedhost for perceptual quality or robustness constraints. One approach, forexample, is to modulate the host so that it satisfies a perceptualquality metric as determined by perceptual model (e.g., visibilitymodel) for embedding locations across the signal. Another approach is tomodulate the host so that it satisfies a robustness metric across thesignal. Yet another is to modulate the host according to both therobustness metric and perceptual quality metric derived for eachembedding location. The incorporated documents provide examples of thesetechniques. Below, we highlight a few examples.

For color images, the perceptual analyzer generates a perceptual modelthat evaluates visibility of an adjustment to the host by the embedderand sets levels of controls to govern the adjustment (e.g., levels ofadjustment per color direction, and per masking region). This mayinclude evaluating the visibility of adjustments of the color at anembedding location (e.g., units of noticeable perceptual difference incolor direction in terms of CIE Lab values), Contrast SensitivityFunction (CSF), spatial masking model (e.g., using techniques describedby Watson in US Published Patent Application No. US 2006-0165311 A1,which is incorporated by reference herein in its entirety), etc. One wayto approach the constraints per embedding location is to combine thedata with the host at embedding locations and then analyze thedifference between the encoded host with the original. The renderingprocess may be modeled digitally to produce a modeled version of thesparse signal as it will appear when rendered. The perceptual model thenspecifies whether an adjustment is noticeable based on the differencebetween a visibility threshold function computed for an embeddinglocation and the change due to embedding at that location. The embedderthen can change or limit the amount of adjustment per embedding locationto satisfy the visibility threshold function. Of course, there arevarious ways to compute adjustments that satisfy a visibility threshold,with different sequences of operations. See, e.g., our U.S. applicationSer. Nos. 14/616,686, 14/588,636 and 13/975,919, Patent ApplicationPublication 20100150434, and U.S. Pat. No. 7,352,878.

The embedder also computes a robustness model in some embodiments. Thecomputing a robustness model may include computing a detection metricfor an embedding location or region of locations. The approach is tomodel how well the decoder will be able to recover the data signal atthe location or region. This may include applying one or more decodeoperations and measurements of the decoded signal to determine howstrong or reliable the extracted signal. Reliability and strength may bemeasured by comparing the extracted signal with the known data signal.Below, we detail several decode operations that are candidates fordetection metrics within the embedder. One example is an extractionfilter which exploits a differential relationship between a sparse dotand neighboring content to recover the data signal in the presence ofnoise and host signal interference. At this stage of encoding, the hostinterference is derivable by applying an extraction filter to themodulated host. The extraction filter models data signal extraction fromthe modulated host and assesses whether a detection metric is sufficientfor reliable decoding. If not, the sparse signal may be re-inserted withdifferent embedding parameters so that the detection metric is satisfiedfor each region within the host image where the sparse signal isapplied.

Detection metrics may be evaluated such as by measuring signal strengthas a measure of correlation between the modulated host and variable orfixed data components in regions of the host, or measuring strength as ameasure of correlation between output of an extraction filter andvariable or fixed data components. Depending on the strength measure ata location or region, the embedder changes the amount and location ofhost signal alteration to improve the correlation measure. These changesmay be particularly tailored so as to establish sufficient detectionmetrics for both the payload and synchronization components of thesparse signal within a particular region of the host image.

The robustness model may also model distortion expected to be incurredby the modulated host, apply the distortion to the modulated host, andrepeat the above process of measuring visibility and detection metricsand adjusting the amount of alterations so that the data signal willwithstand the distortion. See, e.g., Ser. Nos. 14/616,686, 14/588,636and 13/975,919 for image related processing; each of these patentdocuments is hereby incorporated herein by reference.

This modulated host is then output as an output signal 162, with anembedded data channel. The operation of combining also may occur in theanalog realm where the data signal is transformed to a rendered form,such as a layer of ink, including an overprint or under print, or astamped, etched or engraved surface marking. In the case of videodisplay, one example is a data signal that is combined as a graphicoverlay to other video content on a video display by a display driver.Another example is a data signal that is overprinted as a layer ofmaterial, engraved in, or etched onto a substrate, where it may be mixedwith other signals applied to the substrate by similar or other markingmethods. In these cases, the embedder employs a predictive model ofdistortion and host signal interference, and adjusts the data signalstrength so that it will be recovered more reliably. The predictivemodeling can be executed by a classifier that classifies types of noisesources or classes of host signals and adapts signal strength andconfiguration of the data pattern to be more reliable to the classes ofnoise sources and host signals.

The output 162 from the embedder signal typically incurs various formsof distortion through its distribution or use. This distortion is whatnecessitates robust encoding and complementary decoding operations torecover the data reliably.

Turning to FIG. 2, a signal decoder receives a suspect host signal 200and operates on it with one or more processing stages to detect a datasignal, synchronize it, and extract data. The detector is paired withinput device in which a sensor or other form of signal receiver capturesan analog form of the signal and an analog to digital converter convertsit to a digital form for digital signal processing. Though aspects ofthe detector may be implemented as analog components, e.g., such aspreprocessing filters that seek to isolate or amplify the data channelrelative to noise, much of the signal decoder is implemented as digitalsignal processing modules.

The detector 202 is a module that detects presence of the sparse signaland other signaling layers. The incoming image is referred to as asuspect host because it may not have a data channel or may be sodistorted as to render the data channel undetectable. The detector is incommunication with a protocol selector 204 to get the protocols it usesto detect the data channel. It may be configured to detect multipleprotocols, either by detecting a protocol in the suspect signal and/orinferring the protocol based on attributes of the host signal or othersensed context information. A portion of the data signal may have thepurpose of indicating the protocol of another portion of the datasignal. As such, the detector is shown as providing a protocol indicatorsignal back to the protocol selector 204.

The synchronizer module 206 synchronizes the incoming signal to enabledata extraction. Synchronizing includes, for example, determining thedistortion to the host signal and compensating for it. This processprovides the location and arrangement of encoded data elements of asparse signal within an image.

The data extractor module 208 gets this location and arrangement and thecorresponding protocol and demodulates a data signal from the host. Thelocation and arrangement provide the locations of encoded data elements.The extractor obtains estimates of the encoded data elements andperforms a series of signal decoding operations.

As detailed in examples below and in the incorporated documents, thedetector, synchronizer and data extractor may share common operations,and in some cases may be combined. For example, the detector andsynchronizer may be combined, as initial detection of a portion of thedata signal used for synchronization indicates presence of a candidatedata signal, and determination of the synchronization of that candidatedata signal provides synchronization parameters that enable the dataextractor to apply extraction filters at the correct orientation, scaleand start location. Similarly, data extraction filters used within dataextractor may also be used to detect portions of the data signal withinthe detector or synchronizer modules. The decoder architecture may bedesigned with a data flow in which common operations are re-usediteratively, or may be organized in separate stages in pipelined digitallogic circuits so that the host data flows efficiently through thepipeline of digital signal operations with minimal need to movepartially processed versions of the host data to and from a sharedmemory, such as a RAM memory.

Signal Generator

FIG. 3 is a flow diagram illustrating operations of a signal generator.Each of the blocks in the diagram depict processing modules thattransform the input auxiliary data (e.g., the payload) into a datasignal structure. For a given protocol, each block provides one or moreprocessing stage options selected according to the protocol. Inprocessing module 300, the auxiliary data is processed to compute errordetection bits, e.g., such as a Cyclic Redundancy Check, Parity, or likeerror detection message symbols. Additional fixed and variable messagesused in identifying the protocol and facilitating detection, such assynchronization signals may be added at this stage or subsequent stages.

Error correction encoding module 302 transforms the message symbols intoan array of encoded message elements (e.g., binary or M-ary elements)using an error correction method. Example include block codes,convolutional codes, etc.

Repetition encoding module 304 repeats the string of symbols from theprior stage to improve robustness. For example, certain message symbolsmay be repeated at the same or different rates by mapping them tomultiple locations within a unit area of the data channel (e.g., oneunit area being a tile of bit cells, bumps or “waxels,” as describedfurther below).

Next, carrier modulation module 306 takes message elements of theprevious stage and modulates them onto corresponding carrier signals.For example, a carrier might be an array of pseudorandom signalelements. For a sparse signal, this may include equal number of binaryone and binary zero elements. These may correspond to “ink” and “no ink”elements of the sparse signal. The data elements of a sparse signal mayalso be multi-valued. In this case, M-ary or multi-valued encoding ispossible at each sparse signal element, through use of different colors,ink quantity, dot patterns or shapes. Sparse signal application is notconfined to lightening or darkening an object at a sparse elementlocation (e.g., luminance or brightness change). Various adjustments maybe made to effect a change in an optical property, like luminance. Theseinclude modulating thickness of a layer, surface shape (surfacedepression or peak), translucency of a layer, etc. Other opticalproperties may be modified to represent the sparse element, such aschromaticity shift, change in reflectance angle, polarization angle, orother forms optical variation. As noted, limiting factors include boththe limits of the marking or rendering technology and ability of acapture device to detect changes in optical properties encoded in thesparse signal. We elaborate further on signal configurations below.

Mapping module 308 maps signal elements of each modulated carrier signalto locations within the channel. In the case where a digital host signalis provided, the locations correspond to embedding locations within thehost signal. The embedding locations may be in one or more coordinatesystem domains in which the host signal is represented within a memoryof the signal encoder. The locations may correspond to regions in aspatial domain, temporal domain, frequency domain, or some othertransform domain. Stated another way, the locations may correspond to avector of host signal features at which the sparse signal element isinserted.

Various detailed examples of protocols and processing stages of theseprotocols are provided in our prior work, such as our U.S. Pat. Nos.6,614,914, 5,862,260, 6,345,104, 6,993,152 and 7,340,076, which arehereby incorporated by reference in their entirety, and US PatentPublication 20100150434, previously incorporated. More background onsignaling protocols, and schemes for managing compatibility amongprotocols, is provided in U.S. Pat. No. 7,412,072, which is herebyincorporated by reference in its entirety.

The above description of signal generator module options demonstratesthat the form of the sparse signal used to convey the auxiliary datavaries with the needs of the application. As introduced at the beginningof this document, signal design involves a balancing of requiredrobustness, data capacity, and perceptual quality. It also involvesaddressing many other design considerations, including compatibility,print constraints, scanner constraints, etc. We now turn to examinesignal generation schemes, and in particular, schemes that employ sparsesignaling, and schemes for facilitating detection, synchronization anddata extraction of a data signal in a host channel.

One signaling approach, which is detailed in U.S. Pat. Nos. 6,614,914,and 5,862,260, is to map signal elements to pseudo-random locationswithin a channel defined by a domain of a host signal. See, e.g., FIG. 9of U.S. Pat. No. 6,614,914. In particular, elements of a watermarksignal are assigned to pseudo-random embedding locations within anarrangement of sub-blocks within a block (referred to as a “tile”). Theelements of this watermark signal correspond to error correction codedbits output from an implementation of stage 304 of FIG. 3. These bitsare modulated onto a pseudo-random carrier to produce watermark signalelements (block 306 of FIG. 3), which in turn, are assigned to thepseudorandom embedding locations within the sub-blocks (block 308 ofFIG. 3). An embedder module modulates this signal onto a host signal byadjusting host signal values at these locations for each errorcorrection coded bit according to the values of the correspondingelements of the modulated carrier signal for that bit.

The signal decoder estimates each coded bit by accumulating evidenceacross the pseudo-random locations obtained after non-linear filtering asuspect host image. Estimates of coded bits at the sparse signal elementlevel are obtained by applying an extraction filter that estimates thesparse signal element at particular embedding location or region. Theestimates are aggregated through de-modulating the carrier signal,performing error correction decoding, and then reconstructing thepayload, which is validated with error detection.

This pseudo-random arrangement spreads the data signal such that it hasa uniform spectrum across the tile. However, this uniform spectrum maynot be the best choice from a signal communication perspective sinceenergy of a host image may concentrated around DC. Similarly, anauxiliary data channel in high frequency components tends to be moredisturbed by blur or other low pass filtering type distortion than otherfrequency components. We detail a variety of signal arrangements in ourco-pending U.S. patent application Ser. No. 14/724,729, filed May 28,2015, entitled DIFFERENTIAL MODULATION FOR ROBUST SIGNALING ANDSYNCHRONIZATION, and published as US 2016-0217547 A1, which is herebyincorporated by reference in its entirety. This application detailsseveral signaling strategies that may be leveraged in the design ofsparse signals, in conjunction with the techniques in this document.Differential encoding applies to sparse elements by encoding in thedifferential relationship between a sparse element and other signal,such as a background, host image, or other signal components (e.g., async component).

Our U.S. Pat. No. 6,345,104, building on the disclosure of U.S. Pat. No.5,862,260, describes that an embedding location may be modulated byinserting ink droplets at the location to decrease luminance at theregion, or modulating thickness or presence of line art. Additionally,increases in luminance may be made by removing ink or applying a lighterink relative to neighboring ink. It also teaches that a synchronizationpattern may act as a carrier pattern for variable data elements of amessage payload. The synchronization component may be a visible design,within which a sparse or dense data signal is merged. Also, thesynchronization component may be designed to be imperceptible, using themethodology disclosed in U.S. Pat. No. 5,862,260.

In this document, we further revisit the design, encoding and decodingof sparse signals in more detail. As introduced above, one considerationin the design of a sparse signal is the allocation of signal for datacarrying and for synchronization. Another consideration is compatibilitywith other signaling schemes in terms of both encoder and decoderprocessing flow. With respect to the encoder, the sparse encoder shouldbe compatible with various signaling schemes, including dense signaling,so that it each signaling scheme may be adaptively applied to differentregions of an image design, as represented in an image design file,according to the characteristics of those regions. This adaptiveapproach enables the user of the encoder tool to select differentmethods for different regions and/or the encoder tool to be programmedto select automatically a signaling strategy that will provide the mostrobust signal, yet maintain the highest quality image, for the differentregions.

One example of the advantage of this adaptive approach is in productpackaging where a package design has different regions requiringdifferent encoding strategies. One region may be blank, another blankwith text, another with a graphic in solid tones, another with aparticular spot color, and another with variable image content.

With respect to the decoder, this approach simplifies decoderdeployment, as a common decoder can be deployed that decodes varioustypes of data signals, including both dense and sparse signals.

One approach to sparse signal design is to construct the signal to haveoptimal allocation of payload and synchronization components, withoutregard to compatibility with legacy dense signaling protocols. In suchan approach, the signaling techniques for data and synchronization aredeveloped to minimize interference between the variable data carryingand synchronization functions of the sparse signal. For example, if thesparse signal is being designed without needing to be compatible with adense signaling strategy, it can be designed from the start to becomprised as an array of sparse elements, with variable data and syncfunctions. One advantage is that there is no need to apply a thresholdor quantizer to remove aspects of a signal to convert it into a sparseformat.

Another approach is to design a sparse signal to be compatible with alegacy signaling scheme. Within this type of an approach, one can employtechniques to convert a legacy signaling scheme into a sparse signal. Inparticular, in one such approach, the process of generating a sparsesignal begins with a dense watermark signal, and selectively removeselements of it to produce a sparse signal, while retaining sufficientamounts of data and synchronization functionality.

As we detail further below, there are several ways to convert densesignals to sparse signals. Before exploring these methods, we start byfurther considering properties of dense signals relative to sparsesignal. In some cases, the dense signal is comprised of a multi-valuedwatermark tile (e.g., eight bit per pixel image approximating acontinuous signal), which is a block of m by n embedding locations,where m and n are the integer coordinates of embedding locations in atile (e.g., m=n=128, 256, 512, etc.). The value at each tile correspondsto an adjustment to be made to a corresponding location in a host imageto encode the watermark. The tile is repeated contiguously in horizontaland vertical directions over a region of the host image, possibly theentire image. The signal is considered “dense” relative to a sparsesignal, when the adjustments are densely spaced, in contrast to a sparsesignal, where its signal elements are spread apart in the tile. Densesignals are preferred for host signals that are similarly dense,varying, and multi-valued, enabling embedding by adjusting the values ofthe host signal at the embedding locations. A dense embedding enableshigher capacity embedding for both data and sync functions within atile.

Converting a dense signal to a sparse signal still achieves theobjective of reliable signaling due to a couple of characteristics ofthe signal and host. First, the signal is redundant in the tile andacross repeated tiles, so removing a portion of it from each tile leavessufficient signal for reliable and complete recovery of the payload.Signal detection is aggregated across tiles to further assist inreliable recovery, as detailed, for example in U.S. Pat. No. 6,614,914.Second, sparse signaling is adaptively applied where there is lesslikely to be interference with host signal content, and as such, itssparse property is relatively less impacted by interference.

Some approaches to converting dense to sparse signals include, but arenot limited to:

-   -   Quantizing the array of multi-valued signal to produce a sparse        array of elements by quantizing some sub-set of the values to        zero;    -   Selecting a sub-set of a dense signal, with selection being        adapted to retain data signal and sync function within a tile        (keeping in mind that such selection may be implemented across        tile boundaries in a manner that reliable detection can be made        with the aid of extraction from an area larger than that of a        single tile);    -   Selecting locations to retain based on a particular signal        pattern, which may be variable or fixed per tile;    -   Selection or locations based on a pattern of the data signal or        a synchronization signal; and    -   Combinations of the above, where, for example, quantizing        inherently acts to select values to retain and sets the value of        the sparse element.

These methods are not mutually exclusive and may be combined in variousways. The case of using quantization may also include applying a fixedor adaptive threshold operation to convert a multi-valued dense signalto a sparse signal. Use of a threshold operation to generate a sparsesignal is described, for example, in U.S. Pat. No. 6,993,152, which isincorporated by reference above. Below, we describe further detailsthrough examples illustrating various methods.

Whether one starts with a sparse signal or generates one by converting adense signal, it should be noted that techniques for modulating variabledata into the sparse signal can vary quite a bit. Our U.S. Pat. Nos.5,862,260, 6,614,914, and 6,345,104 describe several examples ofmodulation for carrying variable data in image content, and U.S. patentapplication Ser. No. 14/724,729, describes yet additional examples,including differential modulation methods. These documents also describeexplicit and implicit synchronization signals.

As introduced above with reference to FIG. 3, there are stages ofmodulation/de-modulation in the encoder, so it is instructive to clarifydifferent types of modulation. One stage is where a data symbol ismodulated onto an intermediate carrier signal. Another stage is wherethat modulated carrier is inserted into the host by modulating elementsof the host. In the first case, the carrier might be pattern, e.g., apattern in a spatial domain or a transform domain (e.g., frequencydomain). The carrier may be modulated in amplitude, phase, frequency,etc. The carrier may be, as noted, a pseudorandom string of 1's and 0'sor multi-valued elements that is inverted or not (e.g., XOR, or flippedin sign) to carry a payload or sync symbol.

As noted in our application Ser. No. 14/724,729, carrier signals mayhave structures that facilitate both synchronization and variable datacarrying capacity. Both functions may be encoded by arranging signalelements in a host channel so that the data is encoded in therelationship among signal elements in the host. Application Ser. No.14/724,729 specifically elaborates on a technique for modulating, calleddifferential modulation. In differential modulation, data is modulatedinto the differential relationship among elements of the signal. In somewatermarking implementations, this differential relationship isparticularly advantageous because the differential relationship enablesthe decoder to minimize interference of the host signal by computingdifferences among differentially encoded elements. In sparse signaling,there may be little host interference to begin with, as the host signalmay lack information at the embedding location.

Nevertheless, differential modulation may be exploited or the scheme maybe adapted to allow it to be exploited for sparse signaling. Forexample, sparse elements may be designed such that they have adifferential relationship to other elements, either within the sparsesignal (e.g. the sync component), or within the host signal (e.g.,neighboring background of each sparse element). A sparse element where adot of ink is applied, for example, has a differential relationship withneighbors, where no ink is applied. Data and sync signals may beinterleaved so that they have such differential relationships. A sparsesignal may be encoded differentially relative to a uniform or solidtone, where some sparse elements darken the tone (e.g., darker dots),and others lighten it (e.g., lighter holes).

Differential schemes may further be employed as a preliminary stage togenerate a dense multi-valued signal, which in turn is converted to asparse signal using the above described schemes for conversion. Theencoder then converts this dense signal to a sparse signal, maintainingwhere possible, differential relationships.

Another form of modulating data is through selection of differentcarrier signals to carry distinct data symbols. One such example is aset of frequency domain peaks (e.g., impulses in the Fourier magnitudedomain of the signal) or sine waves. In such an arrangement, each setcarries a message symbol. Variable data is encoded by inserting severalsets of signal components corresponding to the data symbols to beencoded. The decoder extracts the message by correlating with differentcarrier signals or filtering the received signal with filter bankscorresponding to each message carrier to ascertain which sets of messagesymbols are encoded at embedding locations.

Having now illustrated methods to modulate data into the watermark(either dense or sparse), we now turn to the issue of designing forsynchronization. For the sake of explanation, we categorizesynchronization as explicit or implicit. An explicit synchronizationsignal is one where the signal is distinct from a data signal anddesigned to facilitate synchronization. Signals formed from a pattern ofimpulse functions, frequency domain peaks or sine waves is one suchexample. An implicit synchronization signal is one that is inherent inthe structure of the data signal.

An implicit synchronization signal may be formed by arrangement of adata signal. For example, in one encoding protocol, the signal generatorrepeats the pattern of bit cells representing a data element. Wesometimes refer to repetition of a bit cell pattern as “tiling” as itconnotes a contiguous repetition of elemental blocks adjacent to eachother along at least one dimension in a coordinate system of anembedding domain. The repetition of a pattern of data tiles or patternsof data across tiles (e.g., the patterning of bit cells in our U.S. Pat.No. 5,862,260) create structure in a transform domain that forms asynchronization template. For example, redundant patterns can createpeaks in a frequency domain or autocorrelation domain, or some othertransform domain, and those peaks constitute a template forregistration. See, for example, our U.S. Pat. No. 7,152,021, which ishereby incorporated by reference in its entirety.

The concepts of explicit and implicit signaling readily merge as bothtechniques may be included in a design, and ultimately, both provide anexpected signal structure that the signal decoder detects to determinegeometric distortion.

In one arrangement for synchronization, the synchronization signal formsa carrier for variable data. In such arrangement, the synchronizationsignal is modulated with variable data. Examples include sync patternsmodulated with data.

Conversely, in another arrangement, that modulated data signal isarranged to form a synchronization signal. Examples include repetitionof bit cell patterns or tiles.

These techniques may be further exploited in sparse signal designbecause the common structure for carrying a variable payload andsynchronizing in the decoder is retained in the sparse design, whileminimizing interference between the signal components that provide thesefunctions. We have developed techniques in which one signal component isa carrier of the other component, and in these techniques, the processof generating a sparse signal produce a signal that performs bothfunctions.

The variable data and sync components of the sparse signal may be chosenso as to be conveyed through orthogonal vectors. This approach limitsinterference between data carrying elements and sync components. In suchan arrangement, the decoder correlates the received signal with theorthogonal sync component to detect the signal and determine thegeometric distortion. The sync component is then filtered out. Next, thedata carrying elements are sampled, e.g., by correlating with theorthogonal data carrier or filtering with a filter adapted to extractdata elements from the orthogonal data carrier. Signal encoding anddecoding, including decoder strategies employing correlation andfiltering are described in our co-pending application Ser. No.14/724,729, and these strategies may be employed to implement thisapproach for sparse signaling.

Additional examples of explicit and implicit synchronization signals areprovided in our previously cited U.S. Pat. Nos. 6,614,914, and5,862,260. In particular, one example of an explicit synchronizationsignal is a signal comprised of a set of sine waves, with pseudo-randomphase, which appear as peaks in the Fourier domain of the suspectsignal. See, e.g., U.S. Pat. Nos. 6,614,914, and 5,862,260, describinguse of a synchronization signal in conjunction with a robust datasignal. Also see U.S. Pat. No. 7,986,807, which is hereby incorporatedby reference in its entirety.

Our US Publication 20120078989, which is hereby incorporated byreference in its entirety, provides additional methods for detecting anembedded signal with this type of structure and recovering rotation,scale and translation from these methods.

Additional examples of implicit synchronization signals, and their use,are provided in U.S. Pat. Nos. 6,614,914, 5,862,260, and applicationSer. No. 14/724,729 as well as U.S. Pat. Nos. 6,625,297 and 7,072,490,which are hereby incorporated by reference in their entirety.

Returning now to sparse signal design, we now provide detailed examplesof sparse signaling techniques. FIG. 4 is a diagram illustrating anembodiment of a sparse signal generator. The signal generator startswith a tile of two signal components, one carrying variable data 400,and one providing a synchronization function 402. The synchronizationsignal is multi-valued per pixel, and it is passed through a quantizer404 to convert it to a signal with fewer levels per pixel. In itssimplest form, the quantizer converts the multi-valued signal into abinary signal, represented as black and white pixels, by a thresholdoperation. The threshold operation for each pixel within a tile compareseach value with a threshold. For binary signals, elements below thethreshold are shown as black here, while elements above the thresholdare white. As noted, this is simply representative of a modulation stateof an optical property at a sparse element, such as darker or lighterrelative to background, and is not particularly limited to renderingblack and white pixels.

The variable data signal 400 is comprised of elements having one of twovalues (e.g., 1 or 0, A, −A). As explained previously, a payload signalmay be transformed into a robust data signal through one or moremodulation stages, e.g., error correction and modulating the errorcorrection coded signal onto a binary carrier signal, which is theapproach used in this embodiment. This modulated carrier is mapped topixel locations within the tile to form data tile 400.

The signal generator of FIG. 4 produces a sparse signal by selectivelycombining elements of data tile 400 with the quantized synchronizationsignal 405. In the embodiment illustrated here, the signal generatorperforms a matrix operation 408 that selectively retains components ofthe data and synchronization tiles, while producing a sparse signaloutput 410. One particular matrix operation to generate dark sparseelements on a lighter background, as shown here, is to compute a logicalAND operation between corresponding pixel locations within the data andsynchronization tiles, such that pixels that are both black at the samecoordinates in each tile remain black in the output. For other inputs(white AND white, black AND white, or white AND black), the output pixelis white at that coordinate.

In this approach, the black pixels of the message signal are retained atall coordinates in the tile where the synchronization signal also has ablack pixel. This technique distributes sparse message elements within atile according the spatial distribution of the synchronization signal.It ensures that there sufficient signal energy to carry the payloadrobustly, while preserving sufficient signal energy for synchronization.It also ensures that the sync signal does not interfere with the sparsemessage elements. This approach may be reversed in the case where theobjective is to generate a sparse signal with light holes against adarker background, with quantization level set appropriately (see laterillustrations of setting thresholds for holes in dark background).

This approach also demonstrates a signal generation method in which amulti-valued component is effectively merged with a binary component.The multi-valued synchronization tile is a spatial domain representationof synchronization template formed by peaks in the frequency domain. Thebinary valued payload carrying component is redundantly encoded anddistributed over the tile. In particular, modulated carrier elements,with an equal number of binary 0 and 1 values are spread evenly over thespatial locations within a tile.

The principles of the method may be applied to alternative signalcomponent inputs. The sync and data components may both be multi-valuedand selectively quantized to a binary or M-ary form prior to mergingwith a selective combination of the components per tile location.Alternatively, both the sync and data components may be binary valuedand merged with a logic operation. Finally, the data component may bemulti-valued and the sync component binary valued, with the datacomponent being quantized prior to merging with the sync component. Thematrix operation to combine elements at tile coordinates may be adaptedto retain sync and data components that are compatible (e.g.,consistently valued or falling within the same quantization bin). Thisapproach allows the generator to form sparse marks with dark elements onlighter background, lighter elements on darker background, or acombination of lighter and darker sparse elements against a mid-leveltone background.

Quantization level (including threshold) and merging function may be setwith adaptive parameters to bias the sparse signal toward data or syncelements.

FIG. 5 is a diagram illustrating a refinement of a sparse signalgenerator like the one in FIG. 4. In this refinement, the output of thesparse signal generator is further processed to transform the sparsesignal elements. The sparse signal tile output from the generator hasdimensions of m by n, where m and n are integer coordinates. For thesake of illustration, we use the example of m=n=128. In preparation forapplication to an object, the tile coordinates are mapped to coordinatesin a target spatial resolution, which is typically expressed in Dots PerInch (DPI). In FIG. 5, the mapping of a tile coordinate corresponds to a4 by 4 block, which means that the effective DPI of the tile isone-fourth the DPI of the target image resolution. For example, thesparse mark tile may be generated to be 75 DPI for insertion into animage at 300 DPI, which translates to each tile coordinate (called awaxel) being a 4 by 4 block (waxel region) of pixels in the imagecoordinate system at 300 DPI. We refer to the region as the “bump” andratio of target image resolution to waxel resolution as the bump size.

In the refinement of FIG. 5, light and dark waxels (500, 502) of thesparse tile are converted to the higher output resolution. Thisconversion enables additional flexibility in the shaping and location ofeach sparse element. Light elements 500 simply convert to 4×4 regions oflight elements (504) at the waxel coordinates. In this example of darksparse elements on light background, the flexibility is in the selectionof the location of the dark element. In the technique of FIG. 5 thelocation of the dark element is pseudo-randomly selected from among 4locations within the center 2×2 square within the 4×4 pixel region of awaxel. These four alternative locations are depicted in blocks 506, 508,510 and 512. The resulting converted sparse signal output is shown asoutput tile 514. This conversion of the sparse input signal (e.g., at 75DPI) to sparse output image signal at the target resolution (e.g., 300DPI) does the following:

-   -   It makes the sparse signal more sparse;    -   It varies the location of the sparse element per embedding        location so that sparse elements are not consistently falling on        horizontal rows and vertical columns of the tile to make the        sparse signal less visually perceptible;    -   It provides some protection against errors introduced by dot        gain of the printing process. Even with errors in dot size and        location due to dot gain, the resulting sparse element is still        located within the correct tile region.

As we explain further below, this sparse output signal may also beconverted further in the RIP process and as applied when printed ormarked onto an object surface, or rendered for display on a screen orprojected image.

FIGS. 6-8 depict histograms of signal components to help illustrateaspects of sparse signal generation from different types of signals.FIG. 6 is a histogram of a digital watermark signal component, withwaxel values that are at one of two different levels (−1, 1). This is anexample of a histogram of a binary antipodal watermark tile, generatedby modulating symbols onto binary antipodal carriers (e.g., a chippingsequence) to create message chips which are mapped pseudo-randomly intolocations across the tile.

FIG. 7 is a histogram of another digital watermark signal component withmulti-level values. This is an example of a spatial domain conversion ofa sync signal tile formed as frequency domain peaks with pseudorandomphase.

FIG. 8 is a histogram of a combination of the digital watermark signalcomponents of FIGS. 6 and 7, also depicting an example of a thresholdoperation to generate a binary image comprising black and white pixelsfrom an image comprised of multi-valued pixels. In this example, thebinary anti-podal signal elements are multiplied by a scale factor of 10and then added to the multi-valued signal component with thedistribution of FIG. 7. To create a sparse signal of darker dots on alighter background, a threshold operation is applied, for example at thethreshold level of the dashed line. Tile elements with a value below thethreshold are set to dark (“black”) and tile elements with a value abovethe threshold are set to light (“white”). This diagram provides agraphical depiction of the sparse signal generation process, whichretains signal of both data carrying and sync components. The manner inwhich the payload is modulated onto carriers with half positive and halfnegative values ensures that the complete signal can be recovered fromwaxels of negative values or waxels of positive values. Here, for darkon light background, the negatively valued waxels are retained.Additionally, sufficient signal energy of the sync signal is alsoretained.

FIG. 9 is a diagram illustrating another refinement of the sparse signalgenerator of FIG. 4. This refinement leverages the same flexibilitydiscussed in connection with FIG. 5 in establishing the sparse dot in abump region. In this case, the sparse dot is located in the bump regionwhere the sync signal level is at its lowest (for dark on lightbackground sparse marks). A similar approach may be used for sparseholes in a darker background, with the sparse hole located where thesynch signal level is highest within the bump region. Because ofpossible dot gain errors, this approach, like the one in FIG. 5, limitsthe selection of dot location to the center four pixels of the bumpregion.

In this variant of the sparse signal generation, the multi-valued synctile (600) is provided at the resolution of the target image (e.g., 300DPI in the continuing example, where waxels are at resolution of 75DPI). The low point within the center 4×4 region of the waxel is atlocation 602. The signal generator places the sparse dot at thislocation 602, which is one (606) of the four candidate locations, 604,606, 608, 610, selectable by the signal generator. This variant providesmore sync signal strength as the sparse signal is generated based on amore detailed analysis of the sync signal level within the waxel.

FIG. 10 is a diagram illustrating application of a threshold to acontinuous watermark signal, and the resulting output for threedifferent thresholds. The top three boxes 620, 622 and 624, illustratehistograms of a continuous watermark signal, with three differentthreshold settings, shown as the dashed lines. Waxels with values belowthe threshold are set to black (darker pixels), while values above areset to white (lighter pixels). The selection of thresholds at thesethree different settings corresponds to the binary image signals 626,628 and 630 shown below each histogram. These diagrams illustrate howthe thresholds may be adjust to set the sparseness of the output signal.The strongest signal output for the continuous signal is where thethreshold is set to zero. FIG. 10 illustrates how the thresholding ofthe continuous watermark signal component controls the distribution ofthe sparse signal elements in the tile. The technique of combining thebinary data signal with the continuous sync signal with a logical ANDoperation has the effect of distributing the data signal according tothe sync signal.

FIG. 11 illustrates a portion of a sparse signal in magnified state toshow dot structure in more detail and set up our explanation of anadditional transformation of the sparse signal. In this particularexample, the image resolution is 300 DPI, and the black squares are 2×2black pixels at the center of the 4×4 waxel region (the “bump” region ofa waxel, where waxels are at 75 DPI). In contrast to the examples ofFIGS. 5 and 9 where a sparse dot is selected from among the 4 pixels ofthe center 2×2 pixels, here all four of the 2×2 pixels are set to black.

FIG. 12 illustrates the sparse signal of FIG. 11, modified to reduce thesignal using a line screen approach. The sparse signal of FIG. 12 isderived from the signal of FIG. 11 by screening back the black dots from100% to 15% with a 175 line screen. This is just one example of how thesparse signal can be made less perceptible by reducing the sparseelements. In this case, the signal is screened back. Another alternativeis to reduce the sparse elements by diluting the ink used to print it(e.g., diluting the ink to create a 15% ink dot).

While we illustrate several examples with black or dark pixels on alight background, the same approach may be applied in different colorinks, including spot colors. Applying the sparse signal with Cyan ink isparticularly effective where the signal is captured with a scanner thatpredominantly captures image signal around a 660 nm wavelength, likemost commercial barcode scanners. The sparse elements may be reduced byscreening, diluted ink, or other reduction techniques applied in the RIPand/or at the time of applying the sparse element to a substrate.

The above examples also show sparse signals are constructed fromcontinuous or multivalued signal components and binary signalcomponents. One component is a variable data carrier while another is async signal. The functions of the components may be reversed.Alternatively, both the data and sync components may be continuoussignals that are selectively quantized and combined.

An alternative sparse signal generation process, for example, is aprocess that begins with sync and data components that are peaks in thefrequency domain. The sync peaks are fixed to form a sync template,whereas the data peaks vary in location in frequency coordinatesaccording to data symbols being encoded. These signal components form acontinuous spatial domain signal when the combined peak signals aretransformed to the spatial domain. This continuous signal is thenconverted to a sparse signal with a threshold operation using theabove-explained approach to generate sparse image signals with both dataand sync components. This approach enables the frequency components forsync and data to be selected so as to minimize interference between thetwo components.

In particular, the frequencies may be chosen to be orthogonal carriersignals, with some for sync, some for data, and some for both sync anddata. The carriers may be modulated with variable data, e.g., usingfrequency shifting, phase shifting, etc.

One benefit of the above techniques is that they are compatible withsignal decoders designed for dense watermark signal counterparts to thesparse signal. For details on decoders, including synchronizationmethods, please see our decoders detailed in U.S. Pat. Nos. 6,614,914,5,862,260, and 6,345,104, and synchronization methods in 20120078989.Synchronization methods and variable data demodulation operate in asimilar fashion as in dense watermark schemes. However, as noted, theextraction filters may be adapted to be optimized for sparse markextraction.

Binary, multi-valued and continuous watermark signal components may alsobe generated using various techniques describe in our co-pendingapplication Ser. No. 14/724,729, which describes various watermarksignal arrangements, differential modulation strategies, andsynchronization approaches. These binary and multi-valued signalcomponents may then be converted to sparse signals using the techniquesdescribed in this document. Though the decoding of such sparse signalsfollows the dense decoding counterparts, we provide an example of theprocessing flow below.

FIG. 13 is a flow diagram illustrating a method of decoding an embeddedwatermark signal and compatible sparse signals. This method wasparticularly designed for differentiation modulation methods inapplication Ser. No. 14/724,729, which is hereby incorporated herein byreference in its entirety, and the following description originates inthat document.

In processing module 700, the method starts by approximating initialtransform parameters, which in this case, include rotation and scale.This module includes preprocessing operations on the suspect signal toprepare it for detection. These operations include transforming thesignal into the domain in which the data signal is encoded and filteringthe signal to reduce interference with the host and other noise. Forexample, if the data channel is encoded in a particular color channel orchannels at a particular resolution and frequency range, module 700transforms the signal into the channel. This may include one or morefiltering stages to remove noise and host signal content outside thechannel of the sparse signal being detected.

Module 700 utilizes a pattern recognition method to approximate initialrotation and scale parameters of the encoded signal structure. Theencoded signal structure has an arrangement that forms a template in thesignal spectrum. There are a variety of pattern matching methods thatmay be employed to approximate the rotation and scale of this templatein the suspect signal. FIG. 14 illustrates one class of such methods inwhich template (labeled “signal”) and the filtered spectrum of thesuspect signal (labeled “measured”) are transformed into a log polar(LP) coordinate system and correlated. The maximum correlation peak inthe correlation within the LP coordinate system is located. The locationof this peak corresponds to the approximate rotation and scale of thetemplate.

In one embodiment for image signaling, module 700 employs the following:

1. Bilateral and Gaussian filters to remove image content whilepreserving the encoded data signal;

2. Grayscale conversion, mean subtraction, and 2D FFT to estimatespatial frequencies;

3. Magnitude and Log-polar transform to equate 2D shift with rotationand scale; and

4. Clip magnitudes and Gaussian filter to remove processing artifactsand noise.

Returning to FIG. 13, signal extraction module 702 extracts anapproximation of the auxiliary data signal using the initial rotationand scale estimate to compensate for rotation and scale. Module 702includes sampling operators (e.g., interpolators) to sample embeddinglocations within the suspect signal, as corrected by the initialrotation and scale. Module 702 also includes an extraction filter thatexploits the relationships used to encode signal elements as describedpreviously to reconstruct an estimate of the data signal.

Module 704 accesses the reconstructed data signal and determines refinedrotation and scale parameters that align it with the template. Module704 computes the spectrum from the reconstructed estimate of the datasignal. From this spectrum, the module 702 obtains a more preciseestimate of rotation and scale. In particular, the location of thespectral peaks in the reconstructed data signal are used to determinethe rotation and scale by determining the geometric transform thataligns them with the template. A variety of pattern matching techniquesmay be used for this process, including the log polar method above,and/or least squares approach of 20120078989, referenced earlier.

Additional refinement modules may be included to determine an estimateof translation of a tile in a suspect signal, as described in20120078989 and U.S. Pat. No. 6,614,914, prior to extracting data.Translation provides the coordinates of the embedding locations within atile of the suspect signal (e.g., start of tile and location of bitcells relative to start of tile). Oversampling may also be used torecover translation.

Data extraction module 706 now extracts a data sequence from embeddinglocations within a tile, which are sampled based on the refinedgeometric transformation parameters (refined rotation, scale, andtranslation). The data sequence extraction applies an extraction filter,again exploiting encoding relationships where appropriate, but this timewith more precise determination of sparse embedding locations.

For payload extraction, the decoder employs a filter adapted to extractan estimate of a data element from a relationship between a sparse dataelement and other signal content. The filter increases the signal tonoise ratio of the data signal relative to noise by leveraging thedifferential relationship among the signals encoding each data element.This filter may be employed both in the synchronization process as wellas the data extraction process. The shape of the filter corresponds tothe area from which it samples signal values and the positionalrelationship of the embedding locations that it evaluates to leveragerelationships.

In some embodiments, the sparse signal decoder applies an extractionfilter called, octaxis, to extract estimates of the sparse signal whilesuppressing interference. For more on such filters, see our U.S. Pat.Nos. 7,076,082 and 8,687,839, which are hereby incorporated by referencein their entirety. Oct axis compares a bit cell with eight neighbors toprovide a compare value (e.g., +1 for positive difference, −1 ornegative difference), and sums the compare values. Differentarrangements of neighbors and weights may be applied to shape the filteraccording to different functions. Another is a cross shaped filter, inwhich a sample interest is compared with an average of horizontalneighbors and vertical neighbors, as descried in U.S. Pat. No.6,614,914, previously incorporated herein.

The output of the extraction filter provides an estimate for each sparseelement. The estimates are aggregated by demodulating the carriersignal. The demodulated payload is input to the error correction decoderprocess. For convolutional coded signals, this is a Viterbi decoder. Theresult is the variable data payload, including error check bits, used tovalidate the variable data field of the payload.

The above description provides a variety of techniques from which manydifferent signaling strategies may be developed. Below, we furtherdescribe how to derive sparse signals of various types, building on theabove framework.

Differential Modulation and Sparseness

When differential modulation is used in conjunction with a sync signalcomponent, the above approaches used for generating sparse marks fromsync and message components also apply.

When differential modulation of the variable data component is used byitself to provide self-sync capabilities, then there is no explicit synccomponent. All of the pixels carry the message signal. These pixels maybe formed so as to have a binary value (−1 or +1), or multiple values(e.g., approximating a continuous signal).

In the case of binary valued pixels, a continuous sync component may beintroduced to provide a means to distribute the data values within atile.

In the case of multi valued pixels, a quantization (including thresholdoperation) may be used to generate a sparse signal from densedifferential modulated input signal. Orthogonal differential modulation(see, e.g., co-pending application Ser. No. 14/724,729) provides a wayto generate sparseness, since the message signal values can take on manyvalues (not just −1 or +1). Here, the thresholding approach can be usedto generate sparseness.

Sparseness without Explicit Sync Component

In some embodiments, the variable data signal may have no explicit synccomponent and have binary valued pixels. It may be made sparse by avariety of methods, such as:

-   -   Randomly white out (or alternatively, black out) different parts        of the message;    -   Use a noise distribution to play a similar role as the sync        signal distribution:        -   Additional information could be conveyed through this noise            distribution;        -   The noise distribution could be different for different            blocks in the image (providing some randomness to the sparse            pattern);        -   Which noise distribution a particular block came from can be            deciphered by computing the conditional probability after            detection;        -   Use knowledge of the protocol (version, error correction            code, error detection code, repetition code and spreading or            modulating with carrier) to determine where to place the            sparse signaling components (i.e., the ink spots on a            lighter background) to obtain optimal SNR for a given            sparseness;        -   Perturb the message signal values at arbitrary locations and            use an objective function (e.g., message correlation) to            determine which perturbations to keep and which to discard.            General Points about Sparse Signals

Recapping, we now provide additional observations and design variations.The distribution of the multi-valued signal component in the spatialdomain provides a control parameter (e.g., threshold) to adjustsparseness. This signal component plays a dominant role in determiningsparseness, with amount of sparseness controlled by the threshold. Thestrength of this signal provides an additional parameter to controlsparseness.

Sparse signals can be encoded by using multi-bit values. These could beprinted using multiple inks (rather than just ink or no ink in the usualcase). This can be achieved using multiple thresholds or quantizationlevels in the histograms (e.g., histograms of FIG. 10.

For a sparse marks in a tiled configuration, the encoder can also varythe pattern of sparse elements in different tiles by choosing a slightlydifferent threshold per tile (or introducing some randomization intopixel location optimization techniques, e.g., FIG. 5).

The sparse mark may be encoded in one or more ink layers. The ink layermay be a spot color already in the design file, or an ink that is added,but selected to best match inks specified in the design. See, e.g.,color match optimization in US 2015-0156369 A1. In otherimplementations, the sparse mark disclosed in this patent document canbe used as the “watermark tile” in FIG. 7 of the US 2015-0156369 A1publication. The sparse mark may also be formed as a weightedcombination of process colors, e.g., CMYK.

Sparse elements may be applied by modulating the optical property of anobject at the sparse element locations according to the sparse signalelement value. Above, we often noted darker or lighter modulationrelative to the background, and there are many ways to make suchmodulation. Examples include adding or removing ink or coatings, orengraving or etching the substrate surface. The shape, thickness ortranslucency of material at a sparse element location may be modified toapply the sparse element.

Laser marking, including laser engraving, in particular is an effectiveway to apply a sparse mark to a wide range of object types andmaterials. Such marking applies to many different industries, includingmobile phone parts (e.g., keypad), plastic translucent parts, electroniccomponents, integrated circuits (IC), electrical appliances,communication products, sanitary ware, tools, accessories, knives,eyeglasses and clocks, jewelry, auto parts, luggage buckle, cookingutensils, stainless steel products and other industries. It applies to avariety of substrate types including metals (including rare metals),engineering plastics, electroplating materials, coating materials,coating materials, plastics, rubber, epoxy resin, ceramic, plastic, ABS,PVC, PES, steel, titanium, copper and other materials.

Laser marking may be applied via handheld devices such as the handheldlaser marking machine model BML-FH from Bodor. This is particularlyuseful in marking various types of objects with identifying information,which can then be read by handheld scanners, e.g., to extract a GTIN ina retail setting.

Sparse marks may be merged with display images via compositing in adisplay buffer of a display driver. They may be implemented as a graphicoverlay and may be combined with other bitmapped images via bit blit(bit-boundary block transfer) operations, which are operations forcombining bitmaps using a raster operator.

Sparse marks may be generated, inserted or transformed in a halftoneconversion operation. Above, we illustrated an example of applying aline screen to sparse elements. Sparse elements may be generated in thehalftone conversion, or may be converted into various dot structurearrangements within the halftone conversion process. Halftone conversionmay be used to generate a sparse element as a cluster or pattern ofdots. This conversion process may transform a sparse dot into halftonedots in a combination of colors, screen angles and dot patterns. Thehalftone conversion may also be adapted to insert sparse mark elementsin areas of an image that are compatible with such insertion (e.g.,uniform or solid tone areas, light backgrounds, dark backgrounds, areasaround text fonts, etc.).

Though these operations may reduce the sparse element, as in the exampleof FIGS. 11-12, they are done in a manner in which signal is retainedand captured using an image scanner compatible with the waxelresolution. In our examples, the sparse element is applied at a higherresolution of image rendering (e.g., 300 DPI or higher) than the waxelresolution (e.g., 75 DPI), yet the decoder can extract the sparse signalfrom lower resolution images because the sparse element, though blurredat lower resolution reading, is still recoverable because the basicencoding relationship of sparse element relative to background isintact.

Sparse marking is compatible with many printing technologies. While notpractical to list them all, we list the following: flexography, gravure,offset (including dry offset), digital, ink jet, dye sublimation,thermal (including direct thermal and thermal transfer), laser, 3Dprinting, Intaglio and relief printing, embossing, photolithographic,lithographic, laser marking, including laser engraving, and laseretching.

Sparse marks are particularly effective for use in connection with labeland receipt printers used in retail. These printers typically usethermal printing to print text on white labels or paper stock forreceipts. Sparse marks may be integrated with text and printed withthermal printers on this type of print substrate. This allows variableinformation about fresh foods and deli items, such as the product SKUand weight to be encoded into the sparse mark or linked to an identifierencoded in the sparse mark and then printed with the thermal printer onan adhesive label or receipt for the item. This identifier may bedynamically linked to the variable information captured for the item sothat the POS scanner can look up the item identifier and its variableinformation to assign a price at retail check out.

Mixing of the sparse signal with under and over printed layers ispossible, and sparse signal insertion among other colors or inks iscontrolled by a blend model. Blend models may be used to achieve adesired output color for the sparse element, taking into account otherinks in the package design. Please see our co-pending application Ser.No. 14/616,686 for more detail on blend models and use of them forwatermark signal encoding. These techniques may be used for achievingdesired color matching (e.g., limiting color match error) or colormodification to encode sparse signal elements among other layers orchannels in a design (e.g., to ensure the modification introduced by thesparse element is visible to a scanner relative to surroundingbackground near the sparse element).

Our sparse signal encoding may also take advantage of various spectralencoding and reading technologies, such as the ones detailed in our USApplication Publication 20150071485, INFORMATION CODING AND DECODING INSPECTRAL DIFFERENCES, which is hereby incorporated by reference in itsentirety. Sparse signals may be encoded in spectral differences betweenthe material used to print sparse elements or holes relative to thematerial of the background.

Sparse elements may also be more effectively encoded and decoded whenused in conjunction with multi-spectral imagers, such as those describedin our PCT application, PCT/US14/66689, published as WO2015077493,entitled SENSOR-SYNCHRONIZED SPECTRALLY-STRUCTURED-LIGHT IMAGING, andcoordinated illumination as described in US Patent ApplicationPublication Nos. 20130329006, and 20150156369, which are all herebyincorporated by reference in their entirety. The latter documentsdescribe imaging devices that employ pulsed light sources and/orspectral filtering to enable capture of different spectral bands. Thesparse mark may be encoded in spectral bands that these devices are welladapted to detect, and further processing may also be used to processimages in the different bands to amplify the sparse signal (e.g.,amplify the difference between sparse elements and its neighboringbackground). Sparse marks may also leverage encoding of sparse signalsin plural chrominance directions, as detailed in our applicationpublication no. 2010-0150434, which is hereby incorporated by referencein its entirety.

Sparse Marks with Narrow-Band Absorption Materials

Sparse marks may also be applied using materials that enhance theirdetection. For example, sparse marks may be applied with a continuous ornon-contiguous “coating,” e.g., a varnish, ink extender, ink primer,binder, aqueous or organic-based coating (e.g., sealants and oils), UVcurable coating, acrylic, laminate, and/or adhesive. The term“non-contiguous” is used herein to mean that the coating does notcontinuously cover a surface area as there will be some areas notincluding any such coating. Sparse marks may also be applied with acontiguous coating, the term “contiguous” is used herein to mean thatthe coating continuously covers a surface area but the sparse marks areproduced as a result of a modulation of the thickness or concentrationof a material in that coating. The modulation may introduce a variancein applied print weight which may or may not fall to zero. (The humaneye is often more sensitive to small changes in hue angle rather thancolor saturation than a standard color space representation would haveus believe. A non-continuous sparse mark may produce a variation in hueangle, whereas a modulation in colorant application weight could producea variation in color saturation that may be less visible to the humanvisual system. Both options are contemplated by our technology.)Consideration of the visual impression of gloss variation can be taken.For example, sparse marks with non-contiguous coatings may result in avariation in surface gloss. At certain angles this can result in anenhancement of the visual perception of the mark. However, contiguouscoatings can be designed not to result in any variation in surfacegloss, even further reducing the level of visual perception.

A coating may be depositing on a substrate in a pattern, preferablyusing an additive printing technology. In one example, dry-offset,wet-offset or flexography printing can be used. In another case printingmay include a variety of marking technologies, including engraving,etching, stamping, etc. as there are a variety of ways to impart acoating to a substrate. In some cases, the coating is applied in acontinuous manner, except for providing for sparse “holes” in thecoating, e.g., such as in a pattern resembling a negative photographicimage.

A coating is preferably clear, but sometimes may have a slight amber orcolor hue, and preferably the coating does not absorb light in thevisible spectrum (e.g., 380 nm-710 nm). The coating preferably includesmaterials (sometimes referred to herein as “additives”) such as powders,solutions, liquid crystals, micas, pigments and/or dyes to enhance thedetectability of sparse elements relative to their background orunderlying areas. The “additives” may be dispersed (e.g., in the case ofpowders and pigments) or dissolved (e.g., in the case of dyes) in an inkor coating vehicle. The fact that the particles are dispersed (ratherthan clumped) can be important if using some nanotechnologies such asQuantum Dots. Such nanomaterials have the potential to produce aconsistently narrow emission spectra as a fluorescence technology.

The coating may be inserted as a print layer to apply sparse signalelements. To illustrate further, we describe embodiments optimized for aspectral response of typical point of sale (POS) barcode scanningequipment, in which the scanning equipment is designed to detectbarcodes from monochrome 2D imagery in a spectral range wavelength at oraround 660 nm or at or around 690 nm (“POS scanner”). This type of POSscanner has difficulty detecting signals encoded in colors of lowabsorption at or around 660 nm (or 690 nm), such as light substrates, aswell as objects in whites, reds or yellows. In addition, it hasdifficulty in artwork with no reflectance at 660 nm (or 690 nm), such asblues, greens and blacks. An example of a 660 nm type of POS scanner isthe 9800i, by Datalogic ADC Inc. (offices in Eugene, Oreg.). Other POSbarcode scanners have different spectral responses, e.g., centered at oraround 690 nm, such as the MP6000 scanner, by Zebra TechnologiesCorporation (offices in Lincolnshire, Ill.). The embodiments employmaterials that preferably do not add objectionable visual differences,yet absorb at or around the narrow-band of a POS scanner. We refer tothese materials as “narrow-band absorption materials.” Typically,narrow-band illumination is created by LED illumination (e.g., redillumination) for POS scanners. In other cases we can use materials thatreflect at or around the narrow-band of the scanner so that the scannersees light in dark backgrounds (e.g., to mark sparse “holes” in a darkbackground). We refer to these materials as “narrow-band reflectingmaterials.” Preferably these materials do not dirty light colors whenapplied, yet have absorption or reflection at or around the narrow-bandof the scanner. A narrow-band absorption material, e.g., which maycorrelate with a narrow-band illumination of a POS scanner, can be addedto a coating for printing or layering on a surface. We refer to acombination of a coating and narrow-band absorption material as a“narrow-band absorption coating” (or “narrow-band absorption varnish,”if the coating is a varnish). Combining the coating and narrow-bandabsorption materials may yield a heterogeneous or homogeneouscombination or mixture, or an emulsion.

FIG. 17A shows an example of an ideal spectral reflectance for a 660 nmnarrow-band absorption material (red-dashed line) relative to whitepaper, 25% Cyan (e.g., a 75% screened back version of Cyan), and a pointof sale (POS) scanner (black line) with a spectral response at or around660 nm. This example narrow-band absorption material provides a response(e.g., absorption) that the red illumination POS scanner can “see,”e.g., at or around 660 nm. The POS scanner will effectively “see” thematerial's absorption since the scanner's spectral response overlaps theabsorption pattern. If a color strongly reflects at a scanner's responsewavelength the scanner ‘sees’ white. Bright yellows, magenta, pink,orange and white are all ‘seen’ as white by a red LED scanner. If acolor has a low reflection at this wavelength (e.g., absorbs thewavelength) the scanner “sees” black. Dark blue, cyan, green, purple andblack are all ‘seen’ as black by the camera. FIG. 17B illustrates thesearrangements. Thus, a narrow-band absorption coating including a lowspectral reflectance at or around 660 nm (or at or around 690 nm) canregister black pixel values to a red LED POS scanner and is suitable forcarrying information signal elements, including sparse signal elements.Of course, different narrow-band absorption materials can be used toaccommodate different wavelength response sources as well.

Examples of narrow-band absorption materials are available from avariety of suppliers, including QCR Solutions, Corp. (Port St. Lucie,Fla., e.g., products VIS680D, VIS660A and VIS637A), Moleculum (CostaMesa, Calif., e.g., product LUM678 and LUM640), Gentex Corp.(Carbondale, Pa., e.g., FILTRON's A Series absorbers), StardustMaterials, LLC (Vancouver, Wash.), and SICPA SA (Lausanne, Switzerland).An absorbance response for QRC Solution's 660 nm narrow-band absorptionmaterial VIS660A is shown in FIG. 17C. (Absorbance and reflectance areinversely related.) Various vendors may make products to order, inaccordance with specified customer requirements, and narrow-bandabsorption needs.

In general, colorants work by the selective absorption of visible light.To do this the colorant molecules exist in a ground and excited state,separated by an allowed transition of an energy compatible with visiblephotons. A large number of colorant molecule classes exist naturally andhave been developed, initially for the textile industry. Furtherdevelopment of technical dyes took place to support the photographicindustry with silver halide sensitizing dyes and color couplers forcolor photography.

The standard “electron in a box” model for photon absorption by amolecule may produce very narrow absorption line spectra. A dye moleculeundergoing an electronic transition may have a fixed size determined bythe chemical constitution. However, the various rotational andvibrational energy states of the molecule may conspire to widen therange of energy level transitions, thus increasing band width. Theseeffects are sometimes seen as “shoulders” on the visible absorptionspectrum.

Even so, colorants can produce comparatively narrow linewidths when insimple situations such as dilute solutions in organic solvents. Suchmaterials are available commercially and examples includephthalocyanine, squarine, rylene, porphoryn, dithiolene, trisaminium.Additional examples can be found in the patent literature, e.g., U.S.Pat. No. 8,227,637, which is hereby incorporated herein in its entirety.There can be, however, some complications when these molecules areplaced in practical situations. These may affect the bandwidth of theabsorption so are pertinent here. By way of example, it is useful toconsider dyes and pigments separately and then consider their relativeattributes.

The minimum bandwidth for dyes in solution tends to be at lowconcentrations in solvents that keep the molecules apart. However, asconcentrations increase there is a tendency for the molecules to formaggregates; dimers, trimers etc. These aggregates can have differentwavelength absorption characteristics and as the aggregates tend toexist as a mixture it can provide additional peaks and/or a widening ofthe absorption spectrum. In some case due to steric hindrance toaggregation of the molecules the aggregation can produce eitherincreases or reduction in bandwidth or absorption wavelength.

When formulated into printing inks and applied to a substrateaggregation can have some effects on absorption wavelength andbandwidth. Two variables influencing aggregation for a particular dyemay be the relative concentrations of dye and residual organics in theprint. For example, a group working on inkjet prints showed thatparameters such as humidity, temperature, solvents, and/or polymers inthe substrate or inks influence the state of dye aggregation. See RSteiger, P-A Brugger, “Photochemical Studies on the Lightfastness ofInk-Jet Systems”, Proc. IS&T's NIP 14 conference, pp 114-117 (1998),which is hereby incorporated herein by reference.

The situation is no less complex with pigments. Pigments includecolorants in a crystalline, amorphous or mixed phase. There are at leasttwo criteria to consider here. 1. The crystal habit. Compounds such ascopper phthalocyanine can exist in a number of crystalline forms and canexist as polymorphs. These can have differences in absorption spectra sothe polymorph can have a wider bandwidth than a crystalographically purevariety. 2. Pigment particle size. Particle size can change a number ofoptical properties, including opacity and hue. As a result the particlesize and particle size distribution of a dispersion may affect theposition and bandwidth of the absorption maximum. We mentioned the usedof Quantum Dots and other nano-particulates earlier. In some cases, theyparticles are considered to be a form of pigment.

In addition to the bandwidth effect differences between dyes andpigments there is also print permanence to consider. In general pigmentshave a better longevity to light, heat, pollutants etc. But even withindyes the degree of aggregation can influence factors such as lightfastness.

Some additional narrow-band absorption materials (e.g., porphines andphthalocyanine, and related molecules) are detailed in various patentdocuments, including U.S. Pat. Nos. 5,998,609, 7,559,983, 7,892,338,8,159,657, 8,840,029, 20120065313, and EP0638614, which are each herebyincorporated herein by reference in their entirety.

One example coating includes a gloss, dull or matte varnish, such asGans Ink and Supply Co. (Portland, Oreg., USA) part nos. 26240, S-1300,A111000 and/or 98692, or other varnish. Another example coating includesa clear extender such as AQ51 Prepared Extender Base from Nazdar Co.(Shawnee, Kans., USA), or other extender. Yet another example coatingincludes a clear ink primer such as Nazdar Co.'s 69097118 UV SPDR CLEARPRIMER, or other clear primer. The varnish may dry by evaporation andmay then contain a resin, e.g., a synthetic compound. Alternatively avarnish may contain the components of the layer such as when apolyurethane is formed from a reaction of an isocyanate and apolyfunctional alcohol, which can solidify into a flexible coating withgood impact resistance.

Synthetic resins are a replacement for the earlier natural compoundssuch as Rosin (a pine tree extract) and Shellac from beetles. A coatingmay include material considered as a continuum from wholly natural towholly synthetic. In the middle are the modified natural products, suchas those derived from cellulose. Another category includes the alkydpolyester resins.

As a print process, a coating can be applied as a liquid which can bewater-based (aqueous), solvent-based, or a UV curable compound. In thelatter case the liquid may include a UV curable monomer. A coatingformulation may optionally contain a number of other components suchas: 1. a matting agent, a liquid or solid intended to modify the surfacecharacteristics of a print. It may reduce the gloss of a surface orincrease the surface roughness; 2. a plasticiser, a substance added to amaterial to increase either softness, flexibility, or extensibility; and3. waxes to further modify the physical properties.

We mentioned above that we prefer a “clear” coating. In some cases,however, adding some colorant to a coating layer may help either take acolor scheme of a design into consideration (e.g., make a color schememore acceptable to a customer) or to make a sparse mark less visible tothe human visual system (HVS).

A dissolved solution (e.g., a dye powder dissolved in a carrier such asmethanol, chloroform or toluene) including narrow-band adsorptionmaterials may be combined with a coating (e.g., a gloss or matte varnishor ink extender). A solution including the carrier and narrow-bandadsorption materials may be a homogeneous or heterogeneous solution, oran emulsion. The concentration of the dissolved solution may beincreased or decreased relative to the coating to yield a relativelystronger or weaker signal element. In an embodiment using a varnish as acoating, and for (wet) offset printing, we prefer a materialconcentration in the range of 3-4 grams of a methanol based solution(e.g., VIS660A) per 1 litter of varnish (e.g., Gans 26240).

One consideration when taking inks to press is the problem ofmetamerism. This is the phenomenon where two different inks can changetheir relative visual appearance with a change in light spectra, forexample going from daylight to fluorescent illumination. This couldrender a pattern more or less visible against another printed area indifferent lighting conditions. Metamerism is discussed in furtherdetail, below.

A reflectance curve for a narrow-band absorption varnish (e.g., Gans'part no. 26240, including a narrow-band material solution) wouldgenerally follow the paper curve in FIG. 17A, but at or around a 3-15%lower reflectance, including the absorption dip at or around 660 nm. Forso-called Flexographic (“Flexo”) printing we prefer a higher materialper varnish concentration, particularly for clear backgrounds. Ofcourse, concentrations can be varied according to printing need, signalrobustness, visibility constraints, etc. Instead of being carried by acoating, a dissolved solution can be combined in a process color, spotcolor, ink or dye.

A narrow-band absorption coating can be laid down according to aprinting plate pattern (a coating plate), e.g., designed to include asparse watermark when printed. The plate pattern will typically includemultiple, redundant instances of the sparse mark. In some cases thesparse mark is configured as a tile, with redundant instances of thetile arranged edge-to-edge, across some or all faces of a packagedesign. Typically, the coating plate will be the last plate applied to asubstrate. A narrow-band absorption coating may be applied to asubstrate according to a pattern of dark areas, e.g., since a POSscanner “sees” the narrow-band absorption material as black. Examplepatterns are shown in FIG. 4 (410), FIG. 5 (514), FIG. 11 or FIG. 12.(Of course, a narrow-band absorption coating maybe applied according toany other sparse digital watermark pattern.) The white areas in thesefigures preferably receive no such narrow-band absorption coating.Hence, the coating is preferably applied in a non-contiguous manner.

A sparse mark laid down with a narrow-band absorption material can beadvantageous deployed in a so-called “dry offset” printing process. Dryoffset printing utilizes a relief printing plate that transfers or“offsets” multiple colors to a rubber pad or “blanket.” The blanket thentransfers an inked image to a printing surface such as plastic beverageand dairy containers, plastic lids, cosmetic tubes, aluminum cans,industrial plastics and metals, etc. The “dry” in dry offset, refers tothe absence of water for dampening or repelling ink in the inkingsystem. This is in contrast to (wet) offset printing or lithographywhere water is used to dampen and repel oil-based ink from the non-printareas of a relief printing plate. Dry offset ink is sometimes cured ontothe substrate using high intensity ultra-violet (UV) light.

There are several constraints with dry offset printing processes. First,colors rarely (if ever) overprint one another. This presents a challengefor some types of digital watermarking, e.g., that employ overprintingof one or more process colors (CMY) to carry a watermark signal.Examples of overprinting tints are provided in, e.g., assignee's USPublished Patent Application No. US 2015-0156369 A1, which is herebyincorporated herein by reference in its entirety. Another constraint isdot-gain control and screening. It is often difficult to preciselycontrol dot size, screen amounts and/or modulate colors on a dry offsetpress. This makes difficult another class of digital watermarking wherecolors may be modulated or screened to convey a signal.

These constraints can be addressed by selectively applying a narrow-bandabsorption coating to a dry offset printed substrate. For example, thenarrow-band absorption coating is applied according to a sparse mark orother encoded signal pattern. A coating plate is designed according tothe sparse mark (or other) pattern, and the narrow-band absorptioncoating is applied to a substrate corresponding to the pattern.

There are a number of colorant types that are readily formulated intoinks for a variety of print processes. A useful example isPhthalocyanine Blue (C I Pigment Blue 15). Chemically, this is copperphthalocyanine and it typically exists in a number of crystalline forms.Pigments such as these can be used for gravure, flexo-water/solvent,screen and offset printing, among other types of printing.

While Phthalocyanine Blue can be incorporated into inks for a number ofprint processes there are items to consider. Some crystalline forms willrecrystallise in some solvents, resulting in a color change. It can alsoprove to be easier to disperse in some ink vehicle systems than others.Phthalocyanine Blue can also be beneficially chemically modified to besoluble for use as a dye. One difference between offset litho inks onone hand and flexo and gravure inks on the other is in the viscosity.Litho inks are typically in a form of a paste while flexo and gravureinks are relatively lower in viscosity and relatively more liquid-based.

One combination worthy of consideration is offset litho with asubsequent flexo overcoat. This is a combination produced where offsetpresses are fitted with in-line flexo coating units. This could workwell, e.g., if a colorant technology is compatible with oil based inks.Another combination would be a fully flexo press. This would be a goodoption for flexible packaging and would allow access to water basedinks. Some digital printing solutions are also candidate printingenvironments which may be able to produce sparse marks with anarrow-band absorbing material. One other printing technology isTonejet, which has enjoyed some success in metal can marking.

These different printing presses can produce a wide variety of printedink thicknesses. Offset litho typically produces a layer thickness ofonly, e.g., a few μm using thin layers of high colorant strength inks tominimize drying requirements. Flexo printing tends to produce thickerlayers than litho and Gravure inks can produce a thicker layer thanoffset and flexo printing. This may be a consideration is using, e.g., acoating modulation technique.

Recall from FIG. 17B that some colors, e.g., Process Blue, black orsaturated colors, have a low reflectivity (absorb) at the response bandof a POS scanner. In this situation, an additive can be combined with acoating to produce more reflectance under the illumination of thescanner light source. Above, we referred to such an additive as a“narrow-band reflecting material.” The material in this case preferablyreflects within the scanner response wavelength so that the scanner seeslight against dark backgrounds (e.g., to mark sparse “holes” in a darkbackground). A narrow-band reflecting material can be combined with acoating to yield a “narrow-band reflecting coating.” Such a coating canbe applied with, e.g., an offset plate over dark areas to convey asparse or dense digital watermark signal.

Holes in a dark background results in a pattern that is the inverse ofthe patterns shown, e.g., in FIG. 4 (410), FIG. 5 (514), FIG. 11 andFIG. 12. That is, the mentioned light holes would correspond to the darkareas in those figures. Please refer to the above discussion includingpositive and negative waxels for proper formatting of a sparse hole in adarker background, e.g., with the sparse hole located where the synchsignal level is highest within a bump region. Another approach inverts adigital watermark signal prior to embedding. Reflected areas thencorresponding to expected dark pixel or area values. So why all the fussover a “sparse” mark vs. a “dense” mark in this narrow-band absorptionmaterial context? One reason is that a coating may have a slightcoloration, e.g., amber or blue. A dense mark applied with an amber (orother) colored coating could be more noticeable compared to sparselydistributing the signal. Another, related, reason is that thenarrow-band absorption material—itself—may include a coloration, e.g.,blue or green. While such a material (e.g., in powder form) is initialdissolved, e.g., into a solution (e.g., including methanol) and thencombined with a coating such as a varnish or an extender, the colorationmay still be slightly noticeable, particularly for a dense signalrelative to a sparse signal. This provides an advantage for a sparsemark over a dense mark. (In one example, the sparse mark conveyed with anon-contiguous coating covers only between 2-20% of a surface whenapplied; preferably, the coating is only applied to 15% or less of thesurface. More preferable is 10% or less. In another example, the coatingcovers only 1-30% of the surface; more preferable is a 1-25% covering ofthe surface. More preferable still is 1-10%.) However, a relativelydense digitally encoded signal is still preferable over other types ofsymbologies, e.g., 1D or 2D barcodes. Depending on the barcodesymbology, the surface area coverage may be greater than 30%; in somecases the area coverage is greater than 40% or more.

Another advantage of an encoded signal applied with narrow-bandabsorption coating is discussed with respect to light colors, e.g.,yellow. Consider a product package including a background area that ispredominately printed with yellow. One watermarking approach would usean overprinted cyan color to convey a watermark in the yellow backgroundarea. (Recall from FIG. 17B that cyan is a good carrier for a signalelement since a red LED scanner “sees” cyan as black pixel elements.)We've found, however, that the combination of yellow overlaid with cyanmay yield a greenish tint. Green is far from yellow in most packagedesigners' minds. A narrow-band absorption coating can be selectivelyapplied according to an encoded signal pattern, which is read by a redLED scanner, but avoids the greenish tint.

An alternative way to introduce some modulation of the absorption around650 nm would be to use metameric yellow colorants. For example, it ispossible to pick two yellow colorants that look identical under astandard illuminant but have significantly different absorptions in the600-700 nm region. Using two colorants in different inks and modulatingthe amounts of each could well produce a modulation to the scanner withlow human visibility, e.g., in a sparse mark pattern.

Rather than modulate a hue angle with the addition of a cyan absorber itmay be possible to modulate saturation. This may place the modulation onthe saturation (radial) axis of the CIELAB color space, a direction inwhich the human visual system is less sensitive.

Some retails offer so-called “family pack” bundles. A family packbundles items together in one package, e.g., cartons of yogurt, cans oftuna, avocados, bread loafs, soup cans, chip bags, tissue boxes, papertowel rolls, etc. Often, a clear plastic wrap is used to bundle theitems together. The wrap may include some printed branding, graphics,text, but often has large transparent areas without ink. These wraps areoften printed with Flexography (“flexo”), a form of printing which usesa flexible relief plate. Flexography lacks the precise dot gain controlfound in most offset printing presses. The open package space and thelack of precise dot gain control make family packs a difficultwatermarking challenge. A sparse mark or other encoded signal placedwith a narrow-band absorption material is one promising solution to thistroublesome medium. The signal can be applied as a coating in openareas. A narrow-band absorption coating appears clear in the wraps openareas, unobtrusive in other areas, yet remains readable by a red LED POSscanner.

In some embodiments, a first coating (without narrow-band absorptionmaterials) is flooded over a substrate surface (in a contiguous manner).Then, a second and narrow-band absorption coating is applied over thefirst coating, e.g., in a sparse mark or other encoded signal pattern(in a non-contiguous manner). This arrangement even further hides theencoded signal since the first coating and the second coating preferablycoincide in color (e.g., clear or amber) and finish (e.g., matte orgloss).

So far we have discussed narrow-band absorption materials having arelatively narrow absorbing spectrum, for example, FIG. 17A and FIG.17C. Another type of absorption material has a step-function spectralresponse, e.g., as shown in FIG. 22. The absorption remains high wellinto the infrared region. For example, such a material may have spectralabsorption at or around 630 nm and continue through 780 nm. In anotherexample, the material includes spectral absorption at or around 660 nm,which continues through at least 880 nm. In still another example, thematerial absorbs at least through 640 nm-980 nm. A step-function typeresponse will accommodate POS scanners that read (or “see”) at leastinto the near-infrared spectrum. Thus, a step-function absorptionmaterial can be combined with a coating, yielding a “step-functionabsorption coating.” Such a coating then can be applied to a surfaceusing, e.g., an offset plate, with a sparse or dense watermark pattern.Of course, a step function response need not have such a long bandwidth.In some cases, an absorption bandwidth that starts somewhere around 600nm and tails off somewhere above 700 nm may suffice. In these cased, andwhen using a RED LED, it is preferable to have a λmax of the dye beabove 650 nm. The classical “electron in a box” model for colorantabsorption suggests that for long absorption wavelengths you need longconjugation lengths in the molecule. For example, some cyanine colorantmolecules can be added to a conjugate chain length to produce acommensurate increase in λmax, often with an increase in bandwidth.

Watermarks printed with such narrow-band or step-function absorption (orreflecting) materials are fragile (e.g., resistant to copying) since atypical broadband illumination scanner (e.g., as employed by a colorphoto copier) would see very little signal. As such, printed objects(e.g., product packages, identification documents, photographs, images,etc.) including encoded signals conveyed with such narrow-band andstep-function absorption materials will be beneficial foranti-counterfeiting and product authentication applications.

Narrowband Excitation and Fluorescence

Now consider a material including so-called narrowband excitation andfluorescence materials. These types of materials include both anexcitation spectrum and a fluorescence spectrum. Basically, a materialis excited in one spectrum, yet emits in another. One example is shownin FIG. 15, which absorbs at or around 660 nm (e.g., absorbs redillumination from one type of POS scanner) and then fluoresces at ahigher wavelength. Another example material is Alexa Fluor 660, with aspectral excitation and emission shown in FIG. 21. Alexa Fluor 660 (“AF660”) is available, e.g., from Thermo Fisher Scientific, Inc., productno. A20007 (Waltham, Mass.). AF 660 includes an excitation spectrum witha peak or maximum at or around 665 nm and an emission spectrum with apeak or maximum at or around 690 nm. Regions with this type of materialappear lighter when printed on top of a low reflectivity region (e.g.,dark blues, black).

Xanthenes are a good example of organic fluorescent compounds whichinclude the common example of fluorescein. They can be functionalized tocontrol the emission wavelength. This is because of their potential fordye sensitized solar cells and dye lasers. Rhodamines are functionalizedXanthenes and are common magenta colorants in printing inks. They cancommonly be spotted in prints by the fluorescence of the magentacontaining areas. They are also used in fluorescence microscopy forbiology. An example microbiology stain is Nile Red,9-diethylamino-5H-benzo[a]phenoxazine-5-one.

Because some fluorescents are designed to absorb higher energy light andtranslate this through different energy levels they may become subjectto light degeneration, showing poor light fastness in some applications.

This sensitivity could be turned around to become a feature.Fluorophores that absorb in the UV make for simple systems in colorterms in that the only tint they impart is through emission. However,the strong UV absorption can cause degeneration problems. Alternatively,systems where the absorption is towards the blue end of the spectrumcould help with other color management issues in some circumstances,moving the tint of the printed area towards a more acceptable value.

Fluorophores are available as dyes or pigments. Although less commonnowadays pigments can be made from fluorescent minerals.

These are a series of predominantly rare earth material compounds thatby 2-photon absorption produce a conversion from long wavelength (lowenergy) absorption to shorter wavelength (higher energy) emission. Thisis up conversion. They can also be engineered to produce 2 photons fromone (higher energy) one. This is down conversion.

Although these materials are likely to have a higher cost thantraditional colorants or fluorescents they may have some interestingattributes. For example, the use of Neodymium doping can produceemission around 660 nm. See J Collins, H Bell, “Intelligent MaterialSolutions, Covert Tagging and Serialization Systems”, Proc. IS&T's NIP29 International Conference on Digital Printing Technologies, pp 153-157(2013), which is hereby incorporated herein by reference in itsentirety. There are also details in the literature of how to processmaterials like this into inks. See J Petersen, J Meruga, A Baride, P SMay, W Cross, J Kellar, “Upconverting Nanoparticle Security Inks Basedon Hansen Solubility Parameters”, Proc. IS&T's NIP 29 InternationalConference on Digital Printing Technologies, pp 383-385 (2014), which ishereby incorporated herein by reference in its entirety.

Fluorescents are well suited for applying sparse “holes” against adarker background. With the 2D imaging barcode POS scanners availabletoday, this approach works by providing an additive that has afluorescence wavelength λ, e.g., 670 nm<λ<900 nm. Depending on the POSscanner, λ may be between 700 nm and 1.5 um. An advantage of this typeof material is that it absorbs light at or around 665 nm and emits lightat a higher wavelength which is not visible to the human eye (see FIG.23). Overprinting this fluorescent dye results in dark colors whichappear unchanged to the human eye, but results in light holes whenviewed by the barcode scanner.

A narrow-band excitation and fluorescent material can also be insertedinto a color separation. For example, if the material is added to amagenta separation then it would enhance robustness without inversion ofa watermark signal. This would enhance robustness across a printedsurface, e.g., product packaging, wherever a watermarked coating or inkis applied.

Quantum dots are a type of material that can be added for someapplications. For example, applications utilizing NIR fluorescenceproperties. Quantum dots are discussed, e.g., in U.S. Pat. No.6,692,031, US Patent Publication No. US 2008-0277626 A1, and XiaoyuCheng, et al., “Colloidal silicon quantum dots: from preparation to themodification of self-assembled monolayers (SAMs) for bio-applications,”Chem. Soc. Rev., 2014, 43, 2680-2700. These patent documents and theCheng et al. article are hereby incorporated herein by reference intheir entirety.

Combating Color Cast

As discussed above, a narrow-band absorption material can be added to anink, e.g., a process color ink, Cyan (C), Magenta (M) or Yellow (Y). Forcolors with high reflectivity at the scanner LED wavelength, anarrow-band absorption material can be added which absorbs at thecentral wavelength of the LED illumination of the scanner (e.g., redillumination). However, adding such a material may introduce a slightcolor cast. A color cast may distract from the original color used in adesign. For example, if the narrow-band absorption material is added toa yellow ink, a slight greenish cast could be introduced.

Color cast introduced by a narrow-band absorption material can be maskedor reduced by adding a fluorescent or phosphorescent material. Thecorresponding fluorescence or phosphorescence will help prevent oroffset a color cast. Various techniques can be used to make thefluorescent or phosphorescent emission undetectable to a POS scanner(e.g., a scanner with red illumination), for example:

-   -   1. Along with an additive that absorbs at or around 660 nm,        include a fluorescent material that absorbs in the Ultraviolet        region (not seen by a red illumination scanner) and emits light        at or around 660 nm; here, the emission spectrum is inverse of        absorption. For example, see FIG. 18 where the dashed red line        represents the narrow-band absorption material and the inverse        black line represents a corresponding fluorescence. The        absorption for the black line material occurs at a lower        wavelength, e.g., in the blue/greens.    -   2. Temporal solution: Add a material that emits about 10 ms        after exposure (see FIG. 19). This would be unnoticed by a        watermark detector if the POS scanner (or watermark detector) is        gated by the pulsed illumination. For example, the POS scanner        can pulse illumination (red pulse in FIG. 19) every 1/40 seconds        or so, and the detector can analyze image data captured 10 ms        after the rising edge of the illumination (green pulse in FIG.        19). Of course, this timing is given by way of example only and        should not limit our inventive principles.

Some possible combinations include, e.g.:

B1. A method of offsetting color casting for a printed package for aretail product, said method comprising:

providing a first additive that absorbs light energy at or around acenter frequency of an illumination source;

providing a second additive that absorbs in the ultra-violet spectrum,yet fluoresces at or around the center frequency of the illuminationsource, wherein a combination of spectral responses of the firstadditive and the second additive offset color casting;

printing the first additive, second additive and a color on the printedpackage, wherein the printing conveys an encoded plural bit signal.

B2. The method of B1 in which the encoded plural bit signal is conveyedwith digital watermarking.

Beyond Sparse Marks

While we prefer to add an encoded signal with sparse marks, oursolutions are not so limited. As mentioned above, a relatively moredensely encoded signal can be advantageously carried with a narrow-bandor step-function absorption material (as well as narrow-band excitationand fluorescence materials). Additional symbologies are now considered.

Consumer packaged goods (e.g., boxes of cereal, cans of soup, etc.)carry 1-D barcoded identifiers, which are typically printed with blackink on a lighter substrate. At checkout, a store clerk (or the customer)must locate the barcode, and manipulate the item to present the barcodeto the point of sale (POS) scanner, in order for a computer to decodethe barcode and identify the item.

Applicant's U.S. Pat. No. 6,804,377 notes that an out-of-phase embeddingtechnique can be employed to make multiple barcode markings on a productvirtually imperceptible. However, that technique is not suited formonochromatic illumination and imaging, as used in conventional POSscanners.

In accordance with one embodiment of the present technology, packagingfor a retail item is printed with multiple barcode markings that can besensed by conventional POS scanners. Ideally, presentation of any faceof the product to the POS scanner will result in successfulidentification of the item. That is, the barcode needn't be firstlocated by a person, and the package then be manipulated to present thebarcode-bearing surface to the scanner. Any face can be presented, and abarcode will be decoded.

Desirably, the barcode marking is effected using a narrow-bandabsorption material that permits other elements of the package artworkto be visible. Yet the barcode marking exhibits a spectral absorptionthat coincides with the spectrum of illumination employed by typical POSsystems (e.g., at or around 660 or at or around 690 nm). Illumination atthat narrow wavelength is absorbed, and appears dark to the scanner.

Packaging for a retail product can be printed to include a narrow-bandabsorption coating (e.g., a varnish layer or extender layer) that has aspectral absorption corresponding, in wavelength, to the redillumination of a POS scanner. This coating is patterned to form 1Dbarcode markings. A single package can be marked to convey multiplebarcodes. Each barcode occupies a rectangular area. In one embodimentplural such identical rectangles are tiled, edge-to-edge, across allfaces of the package. Such an arrangement is conceptually shown in FIG.20, as seen by a red LED scanner. The FIG. 20 package would appear as awhite package, with no barcodes, perhaps with a tint or huecorresponding to the varnish or narrow-band absorption coating, underhuman observation. In other embodiments, barcodes of several differentsizes or types (e.g., 1-D & 2-D barcodes)—and/or several differentangular orientations (e.g., 0 degrees, 30 degrees, 45 degrees and 90degrees)—are printed on a single package with a narrow-band absorptioncoating.

The absence of a narrow slice of the visible light spectrum, in whichthe material absorbs radiation, is relatively small that the layercontributes a tint effect that is generally too small for human viewersto perceive under normal retail conditions (e.g., viewed from ten inchesor more, under fluorescent retail lighting, without an unmarkedcounterpart for comparison).

Materials with broader absorption spectra have more pronounced tintingeffects. These effects can be reduced by diluting the concentration ofthe narrow-band absorption material in the coating (e.g., varnish). Suchdilution reduces the contrast of the mark “seen” by the scanner, butmost barcode detection systems can work with reduced-contrast barcodes.One such compensation involves the addition of a material (e.g.,Europium powder) that fluoresces red, in the notch band.

This gives an effective mechanism to watermark spot colors which havehigh reflectivity at or around 660 nm, which are problematic for achrominance watermark. A chrominance watermark typically uses at leasttwo colors available to balance luminance changes, plus one of thecolors has to absorb at the scanner LED wavelength (typically red atabout 660 nm). A second absorption dye could be added, which has anabsorption peak in blue, which would be measured by a blue LED in thescanner.

The width of a spectral absorption (e.g., sometimes referred to as a“notch”) may depend on the range of illumination that is expected to beencountered. Desirably the spectral notch is 100 or less nanometers inwidth. An illustrative embodiment has a notch of 50 nm in width, whichcan be used with both 632 nm laser illumination, and 690 nm LEDillumination. Other embodiments may have notches of less than 30 nm,e.g., 20 nm or 10 nm. (Width can be measured as the bandwidth at which50% or more of the incident light is absorbed.)

In one particular embodiment, a package is printed with several layers,which may include process colors and/or spot colors laid down on thepackage substrate using conventional printing plates or othertechnologies. Atop these conventional layers is applied a further layer(e.g., a narrow-band absorption coating) that defines the barcodemarkings. This further layer can be applied using the same printingprocess as is used for the other layers, or it can be applied otherwise(e.g., by ink-jet). It is not essential that the barcode printing beapplied as a top layer.

While FIG. 20 shows marking with 1D barcodes, this is not essential; 2Dbarcodes (e.g., QR codes) and other machine-readable data symbologiescan alternatively be employed. For that matter, text can be repeatedlyprinted across surfaces of product packaging, e.g., in a font that isoptimized for machine recognition, such as the OCR-A font.

Some combinations may include:

A1. Printed packaging for a retail product, bearing both artwork andbarcode markings, the barcode markings including plural barcodes,including two or more barcodes conveying the same payload, said two ormore barcodes being printed on said packaging using an ink with aspectral notch of 100 nm or less, which notch is centered at or around660 nm.

A2. The printed packaging of A1 in which said ink has a spectral notchof 50 nm or less.

A3. A system including a point of sale scanner including redillumination, and the printed packaging of A1 or A2.

A4. The system of A3 in which the point of sale scanner includes a 2Dcamera, and a red LED illumination source.

Despite the availability of other symbologies and text, we have foundthat our sparse watermark signal currently provides the best detectionvs. visibility when using narrow-band absorption materials. In fact, 1Dbarcodes laid down, e.g., with a narrow-band absorption coating, oftenlack sufficient detectability (e.g., contrast between the bars andspaces is insufficient) unless the absorption material concentration isheavily increased. But increasing the concentration for 1D barcodedetection often yields undesirable visible artifacts; that is, closeinspection of the surface betrays the barcode's hidden existence. Thesparse mark signal is robust to noisy environments and can be detectedat a relatively lower contrast.

In some embodiments, a retail product is marked both with redundantbarcodes as detailed above, together with digital watermarking thatconveys the same—or different—payload data. Suitable watermarkingtechnologies are known, e.g., from applicant's patent documentsincluding U.S. Pat. No. 6,590,996; 20140052555; 20150156369; Ser. No.14/725,399, filed May 29, 2015 (now U.S. Pat. No. 9,635,378); Ser. No.14/724,729, filed May 28, 2015 (published as US 2016-0217547 A1); andPCT/US15/44904, filed Aug. 12, 2015 (published as WO 2016/025631).Related technology is detailed in applicant's document 62/142,399, filedApr. 2, 2015. Each of the above patent documents is hereby incorporatedherein by reference.

Some gloss effects can be used to produce features that are visible inthe gloss of the print. By printing certain patterns these gloss effectscan be made visible in preferential directions. For example, please seeEP 1 367 810 A2 and EP 1 370 062 A1 (2003), which are each herebyincorporated herein by reference in its entirety. It was shown that thistechnology can utilize the gloss effects of inkjet printing. As anextension, a sparse mark can be applied with changes in gloss effects,which may reduce the human visibility of packaging on retail shelves. Agloss-effect sparse mark can be viewed from a direction predominantly inthe horizontal plane.

Security printing sometimes uses “optically variable features”. Anexample of a printable version would be a mica based ink that wouldcommonly be screen printed. These have a metallic luster. This type ofeffect can also be produced by interference between the top and bottomlayers of a thin film produced by printing. An example of this is thegloss color effects that can be seen on some inkjet prints. Thevariation of color with angle is sometimes known as a silking effect.

Coloration produced by interference effects are of potential interestfor your application as they show angular variation of reflectionwavelength characteristics. There is the potential here to manufacture afeature that enhances the visibility of the marks to the particularwavelength/optical geometry combinations of barcode readers but keep thevisibility low to the human visual system in typical ambient lighting.

An absorbing ink can be printed to define a pattern on glass—or on filmapplied to glass, and used in the embodiments described herein. Asuitable pattern is the “sparse” watermark pattern detailed in thatpattern application. Another is a QR code. Both such patterns can betiled across the film.

One particular arrangement involves plural inks in which differentabsorption dyes are included. A first pattern is printed in an ink thatabsorbs light in a band centered around 460 nm. Second and thirdpatterns are printed with inks that absorb light at bands around 530 nmand 620 nm, respectively. A film printed with three such inked patternscan be laminated to a window and illuminated with white light, ordaylight. A camera viewing the illuminated film will find the firstpattern revealed in the blue channel (460 nm), where the pattern appearsas black (i.e., all incident illumination at that wavelength isabsorbed. Likewise, the second pattern will appear as black in the greenchannel (530 nm), and the third pattern will be evident as black in thered channel (620 nm).

In a particular arrangement, each of these absorption bands is less than60 nanometers in width, and may be less than 30, 15 or 8 nanometers inwidth (width being measured where the attenuation is at least 3 dB).

The three different patterns can target different audiences, e.g., bydistance or angle.

For example, the first printed pattern (e.g., at 460 nm) can comprisefeatures (e.g., watermark element or QR code elemental blocks) that areformed on the film at a small scale—enabling the pattern to be decodedby pedestrian-conveyed cameras located between one and three feet fromthe film. The second pattern (e.g., at 530 nm) can compriseintermediately-scaled features—enabling decoding of that pattern'spayload at distances between three and eight feet from the film. Thethird pattern (e.g., at 620 nm) can comprise large-scaled features,enabling decoding from eight to 25 feet away. The pedestrian'ssmartphone can examine the red, green and blue color channels separately(sequentially or simultaneously), and try to decode from each thepayload of film. The decoder will succeed in reading the encoded datafrom the color channel in which pattern is captured at a decodablescale.

In a different embodiment, the different patterns are tailored forviewing at different angles. For example, a pattern printed with inkthat absorbs at 460 nm can be formed in normal fashion, for viewingstraight-on (e.g., by a first observer whose smartphone is directedperpendicularly to the plane of the glass, that is—normal to the glass).A pattern printed with ink that absorbs at 530 nm can be warped inanticipation of viewing from 30 degrees to the right of normal (i.e.,pre-distorted so that when viewed by a second observer from such angle,the viewing distortion returns the printed pattern to a rectilinearpresentation—like the first observer has). Similarly, a pattern printedwith ink that absorbs at 620 nm can be warped in the opposite manner, inanticipation of viewing from 30 degrees to the left of normal.

Again, the software decoder can examine each of the camera'sred/green/blue color channels to find which one decodes properly.

In some embodiments, all three printed patterns encode the same payload.In other embodiments, it may be desirable for different of the patternsto convey different payloads.

Naturally, the technology can be used with more or less than threeaudiences, by using more or fewer printed patterns.

(Related technology, for targeting different audience members atdifferent distances—or viewing angles—is detailed in applicant's U.S.Pat. No. 8,412,577, which is hereby incorporated herein in itsentirety.)

Operating Environment

The components and operations of the encoder and decoder are implementedin modules. Notwithstanding any specific discussion of the embodimentsset forth herein, the term “module” may refer to software, firmware orcircuitry configured to perform any of the methods, processes, functionsor operations described herein. Software may be embodied as a softwarepackage, code, instructions, instruction sets or data recorded onnon-transitory computer readable storage mediums. Software instructionsfor implementing the detailed functionality can be authored by artisanswithout undue experimentation from the descriptions provided herein,e.g., written in C, C++, Visual Basic, Java, Python, Tcl, Perl, Scheme,Ruby, etc., in conjunction with associated data. Firmware may beembodied as code, instructions or instruction sets or data that arehard-coded (e.g., nonvolatile) in memory devices. As used herein, theterm “circuitry” may include, for example, singly or in any combination,hardwired circuitry, programmable circuitry such as one or more computerprocessors comprising one or more individual instruction processingcores, state machine circuitry, or firmware that stores instructionsexecuted by programmable circuitry. Multi-processor platforms (includingparallel processors) can also be used to carry out the signal processingfeatures of this disclosure, as can multi-core processors.

Applicant's work also includes taking the scientific principles andnatural laws on which the present technology rests, and tying them downin particularly defined implementations. One such implementation iselectronic circuitry that has been custom-designed and manufactured toperform some or all of the embedding and detecting acts, as anapplication specific integrated circuit (ASIC).

To realize such an ASIC implementation, some or all of the technology isfirst implemented using a general purpose computer, using software suchas MatLab (from Mathworks, Inc.). A tool such as HDLCoder (alsoavailable from MathWorks) is next employed to convert the MatLab modelto VHDL (an IEEE standard, and doubtless the most common hardware designlanguage). The VHDL output is then applied to a hardware synthesisprogram, such as Design Compiler by Synopsis, HDL Designer by MentorGraphics, or Encounter RTL Compiler by Cadence Design Systems. Thehardware synthesis program provides output data specifying a particulararray of electronic logic gates that will realize the technology inhardware form, as a special-purpose machine dedicated to such purpose.This output data is then provided to a semiconductor fabricationcontractor, which uses it to produce the customized silicon part.(Suitable contractors include TSMC, Global Foundries, and ONSemiconductors.)

For the sake of illustration, FIG. 16 is a diagram of an electronicdevice in which the components of the above encoder and decoderembodiments may be implemented. It is not intended to be limiting, asthe embodiments may be implemented in other device architectures orelectronic circuitry.

Referring to FIG. 16, a system for an electronic device includes bus100, to which many devices, modules, etc., (each of which may begenerically referred as a “component”) are communicatively coupled. Thebus 100 may combine the functionality of a direct memory access (DMA)bus and a programmed input/output (PIO) bus. In other words, the bus 100may facilitate both DMA transfers and direct CPU read and writeinstructions. In one embodiment, the bus 100 is one of the AdvancedMicrocontroller Bus Architecture (AMBA) compliant data buses. AlthoughFIG. 16 illustrates an embodiment in which all components arecommunicatively coupled to the bus 100, it will be appreciated that oneor more sub-sets of the components may be communicatively coupled to aseparate bus in any suitable or beneficial manner, and that anycomponent may be communicatively coupled to two or more buses in anysuitable or beneficial manner. Although not illustrated, the electronicdevice can optionally include one or more bus controllers (e.g., a DMAcontroller, an I2C bus controller, or the like or any combinationthereof), through which data can be routed between certain of thecomponents.

The electronic device also includes a CPU 102. The CPU 102 may be anymicroprocessor, mobile application processor, etc., known in the art(e.g., a Reduced Instruction Set Computer (RISC) from ARM Limited, theKrait CPU product-family, any X86-based microprocessor available fromthe Intel Corporation including those in the Pentium, Xeon, Itanium,Celeron, Atom, Core i-series product families, etc.). The CPU 102 runsan operating system of the electronic device, runs application programs(e.g., mobile apps such as those available through applicationdistribution platforms such as the Apple App Store, Google Play, etc.)and, optionally, manages the various functions of the electronic device.The CPU 102 may include or be coupled to a read-only memory (ROM) (notshown), which may hold an operating system (e.g., a “high-level”operating system, a “real-time” operating system, a mobile operatingsystem, or the like or any combination thereof) or other device firmwarethat runs on the electronic device. The electronic device may alsoinclude a volatile memory 104 electrically coupled to bus 100. Thevolatile memory 104 may include, for example, any type of random accessmemory (RAM). Although not shown, the electronic device may furtherinclude a memory controller that controls the flow of data to and fromthe volatile memory 104. The electronic device may also include astorage memory 106 connected to the bus. The storage memory 106typically includes one or more non-volatile semiconductor memory devicessuch as ROM, EPROM and EEPROM, NOR or NAND flash memory, or the like orany combination thereof, and may also include any kind of electronicstorage device, such as, for example, magnetic or optical disks. Inembodiments of the present invention, the storage memory 106 is used tostore one or more items of software. Software can include systemsoftware, application software, middleware (e.g., Data DistributionService (DDS) for Real Time Systems, MER, etc.), one or more computerfiles (e.g., one or more data files, configuration files, library files,archive files, etc.), one or more software components, or the like orany stack or other combination thereof Examples of system softwareinclude operating systems (e.g., including one or more high-leveloperating systems, real-time operating systems, mobile operatingsystems, or the like or any combination thereof), one or more kernels,one or more device drivers, firmware, one or more utility programs(e.g., that help to analyze, configure, optimize, maintain, etc., one ormore components of the electronic device), and the like. Applicationsoftware typically includes any application program that helps userssolve problems, perform tasks, render media content, retrieve (oraccess, present, traverse, query, create, organize, etc.) information orinformation resources on a network (e.g., the World Wide Web), a webserver, a file system, a database, etc. Examples of software componentsinclude device drivers, software CODECs, message queues or mailboxes,databases, etc. A software component can also include any other data orparameter to be provided to application software, a web application, orthe like or any combination thereof. Examples of data files includeimage files, text files, audio files, video files, haptic signaturefiles, and the like.

Also connected to the bus 100 is a user interface module 108. The userinterface module 108 is configured to facilitate user control of theelectronic device. Thus the user interface module 108 may becommunicatively coupled to one or more user input devices 110. A userinput device 110 can, for example, include a button, knob, touch screen,trackball, mouse, microphone (e.g., an electret microphone, a MEMSmicrophone, or the like or any combination thereof), an IR orultrasound-emitting stylus, an ultrasound emitter (e.g., to detect usergestures, etc.), one or more structured light emitters (e.g., to projectstructured IR light to detect user gestures, etc.), one or moreultrasonic transducers, or the like or any combination thereof.

The user interface module 108 may also be configured to indicate, to theuser, the effect of the user's control of the electronic device, or anyother information related to an operation being performed by theelectronic device or function otherwise supported by the electronicdevice. Thus the user interface module 108 may also be communicativelycoupled to one or more user output devices 112. A user output device 112can, for example, include a display (e.g., a liquid crystal display(LCD), a light emitting diode (LED) display, an active-matrix organiclight-emitting diode (AMOLED) display, an e-ink display, etc.), a light,a buzzer, a haptic actuator, a loud speaker, or the like or anycombination thereof.

Generally, the user input devices 110 and user output devices 112 are anintegral part of the electronic device; however, in alternateembodiments, any user input device 110 (e.g., a microphone, etc.) oruser output device 112 (e.g., a loud speaker, haptic actuator, light,display, or printer) may be a physically separate device that iscommunicatively coupled to the electronic device (e.g., via acommunications module 114). A printer encompasses many different devicesfor applying our encoded signals to objects, such as 2D and 3D printers,etching, engraving, embossing, laser marking, etc.

Although the user interface module 108 is illustrated as an individualcomponent, it will be appreciated that the user interface module 108 (orportions thereof) may be functionally integrated into one or more othercomponents of the electronic device (e.g., the CPU 102, the sensorinterface module 130, etc.).

Also connected to the bus 100 is an image signal processor 116 and agraphics processing unit (GPU) 118. The image signal processor (ISP) 116is configured to process imagery (including still-frame imagery, videoimagery, or the like or any combination thereof) captured by one or morecameras 120, or by any other image sensors, thereby generating imagedata. General functions typically performed by the ISP 116 can includeBayer transformation, demosaicing, noise reduction, image sharpening, orthe like or any combination thereof. The GPU 118 can be configured toprocess the image data generated by the ISP 116, thereby generatingprocessed image data. General functions typically performed by the GPU118 include compressing image data (e.g., into a JPEG format, an MPEGformat, or the like or any combination thereof), creating lightingeffects, rendering 3D graphics, texture mapping, calculating geometrictransformations (e.g., rotation, translation, etc.) into differentcoordinate systems, etc. and send the compressed video data to othercomponents of the electronic device (e.g., the volatile memory 104) viabus 100. The GPU 118 may also be configured to perform one or more videodecompression or decoding processes. Image data generated by the ISP 116or processed image data generated by the GPU 118 may be accessed by theuser interface module 108, where it is converted into one or moresuitable signals that may be sent to a user output device 112 such as adisplay, printer or speaker.

Also coupled the bus 100 is an audio I/O module 122, which is configuredto encode, decode and route data to and from one or more microphone(s)124 (any of which may be considered a user input device 110) and loudspeaker(s) 126 (any of which may be considered a user output device110). For example, sound can be present within an ambient, auralenvironment (e.g., as one or more propagating sound waves) surroundingthe electronic device. A sample of such ambient sound can be obtained bysensing the propagating sound wave(s) using one or more microphones 124,and the microphone(s) 124 then convert the sensed sound into one or morecorresponding analog audio signals (typically, electrical signals),thereby capturing the sensed sound. The signal(s) generated by themicrophone(s) 124 can then be processed by the audio I/O module 122(e.g., to convert the analog audio signals into digital audio signals)and thereafter output the resultant digital audio signals (e.g., to anaudio digital signal processor (DSP) such as audio DSP 128, to anothermodule such as a song recognition module, a speech recognition module, avoice recognition module, etc., to the volatile memory 104, the storagememory 106, or the like or any combination thereof). The audio I/Omodule 122 can also receive digital audio signals from the audio DSP128, convert each received digital audio signal into one or morecorresponding analog audio signals and send the analog audio signals toone or more loudspeakers 126. In one embodiment, the audio I/O module122 includes two communication channels (e.g., so that the audio I/Omodule 122 can transmit generated audio data and receive audio datasimultaneously).

The audio DSP 128 performs various processing of digital audio signalsgenerated by the audio I/O module 122, such as compression,decompression, equalization, mixing of audio from different sources,etc., and thereafter output the processed digital audio signals (e.g.,to the audio I/O module 122, to another module such as a songrecognition module, a speech recognition module, a voice recognitionmodule, etc., to the volatile memory 104, the storage memory 106, or thelike or any combination thereof). Generally, the audio DSP 128 mayinclude one or more microprocessors, digital signal processors or othermicrocontrollers, programmable logic devices, or the like or anycombination thereof. The audio DSP 128 may also optionally include cacheor other local memory device (e.g., volatile memory, non-volatile memoryor a combination thereof), DMA channels, one or more input buffers, oneor more output buffers, and any other component facilitating thefunctions it supports (e.g., as described below). In one embodiment, theaudio DSP 128 includes a core processor (e.g., an ARM® AudioDE™processor, a Hexagon processor (e.g., QDSP6V5A)), as well as a datamemory, program memory, DMA channels, one or more input buffers, one ormore output buffers, etc. Although the audio I/O module 122 and theaudio DSP 128 are illustrated as separate components, it will beappreciated that the audio I/O module 122 and the audio DSP 128 can befunctionally integrated together. Further, it will be appreciated thatthe audio DSP 128 and other components such as the user interface module108 may be (at least partially) functionally integrated together.

The aforementioned communications module 114 includes circuitry,antennas, sensors, and any other suitable or desired technology thatfacilitates transmitting or receiving data (e.g., within a network)through one or more wired links (e.g., via Ethernet, USB, FireWire,etc.), or one or more wireless links (e.g., configured according to anystandard or otherwise desired or suitable wireless protocols ortechniques such as Bluetooth, Bluetooth Low Energy, WiFi, WiMAX, GSM,CDMA, EDGE, cellular 3G or LTE, Li-Fi (e.g., for IR- or visible-lightcommunication), sonic or ultrasonic communication, etc.), or the like orany combination thereof. In one embodiment, the communications module114 may include one or more microprocessors, digital signal processorsor other microcontrollers, programmable logic devices, or the like orany combination thereof. Optionally, the communications module 114includes cache or other local memory device (e.g., volatile memory,non-volatile memory or a combination thereof), DMA channels, one or moreinput buffers, one or more output buffers, or the like or anycombination thereof. In one embodiment, the communications module 114includes a baseband processor (e.g., that performs signal processing andimplements real-time radio transmission operations for the electronicdevice).

Also connected to the bus 100 is a sensor interface module 130communicatively coupled to one or more sensors 132. A sensor 132 can,for example, include an accelerometer (e.g., for sensing acceleration,orientation, vibration, etc.), a magnetometer (e.g., for sensing thedirection of a magnetic field), a gyroscope (e.g., for tracking rotationor twist), a barometer (e.g., for sensing altitude), a moisture sensor,an ambient light sensor, an IR or UV sensor or other photodetector, apressure sensor, a temperature sensor, an acoustic vector sensor (e.g.,for sensing particle velocity), a galvanic skin response (GSR) sensor,an ultrasonic sensor, a location sensor (e.g., a GPS receiver module,etc.), a gas or other chemical sensor, or the like or any combinationthereof. Although separately illustrated in FIG. 16, any camera 120 ormicrophone 124 can also be considered a sensor 132. Generally, a sensor132 generates one or more signals (typically, electrical signals) in thepresence of some sort of stimulus (e.g., light, sound, moisture,gravitational field, magnetic field, electric field, etc.), in responseto a change in applied stimulus, or the like or any combination thereof.In one embodiment, all sensors 132 coupled to the sensor interfacemodule 130 are an integral part of the electronic device; however, inalternate embodiments, one or more of the sensors may be physicallyseparate devices communicatively coupled to the electronic device (e.g.,via the communications module 114). To the extent that any sensor 132can function to sense user input, then such sensor 132 can also beconsidered a user input device 110. The sensor interface module 130 isconfigured to activate, deactivate or otherwise control an operation(e.g., sampling rate, sampling range, etc.) of one or more sensors 132(e.g., in accordance with instructions stored internally, or externallyin volatile memory 104 or storage memory 106, ROM, etc., in accordancewith commands issued by one or more components such as the CPU 102, theuser interface module 108, the audio DSP 128, the cue detection module134, or the like or any combination thereof). In one embodiment, sensorinterface module 130 can encode, decode, sample, filter or otherwiseprocess signals generated by one or more of the sensors 132. In oneexample, the sensor interface module 130 can integrate signals generatedby multiple sensors 132 and optionally process the integrated signal(s).Signals can be routed from the sensor interface module 130 to one ormore of the aforementioned components of the electronic device (e.g.,via the bus 100). In another embodiment, however, any signal generatedby a sensor 132 can be routed (e.g., to the CPU 102), the before beingprocessed.

Generally, the sensor interface module 130 may include one or moremicroprocessors, digital signal processors or other microcontrollers,programmable logic devices, or the like or any combination thereof. Thesensor interface module 130 may also optionally include cache or otherlocal memory device (e.g., volatile memory, non-volatile memory or acombination thereof), DMA channels, one or more input buffers, one ormore output buffers, and any other component facilitating the functionsit supports (e.g., as described above). In one embodiment, the sensorinterface module 130 may be provided as the “Sensor Core” (SensorsProcessor Subsystem (SPS)) from Qualcomm, the “frizz” from Megachips, orthe like or any combination thereof. Although the sensor interfacemodule 130 is illustrated as an individual component, it will beappreciated that the sensor interface module 130 (or portions thereof)may be functionally integrated into one or more other components (e.g.,the CPU 102, the communications module 114, the audio I/O module 122,the audio DSP 128, the cue detection module 134, or the like or anycombination thereof).

CONCLUDING REMARKS

Having described and illustrated the principles of the technology withreference to specific implementations, it will be recognized that thetechnology can be implemented in many other, different, forms. Toprovide a comprehensive disclosure without unduly lengthening thespecification, applicants incorporate by reference—in their entirety—thepatents and patent applications referenced above.

The methods, processes, and systems described above may be implementedin hardware, software or a combination of hardware and software. Forexample, the signal processing operations described above may beimplemented as instructions stored in a memory and executed in aprogrammable computer (including both software and firmwareinstructions), implemented as digital logic circuitry in a specialpurpose digital circuit, or combination of instructions executed in oneor more processors and digital logic circuit modules. The methods andprocesses described above may be implemented in programs executed from asystem's memory (a computer readable medium, such as an electronic,optical or magnetic storage device). The methods, instructions andcircuitry operate on electronic signals, or signals in otherelectromagnetic forms. These signals further represent physical signalslike image signals captured in image sensors, audio captured in audiosensors, as well as other physical signal types captured in sensors forthat type. These electromagnetic signal representations are transformedto different states as detailed above to detect signal attributes,perform pattern recognition and matching, encode and decode digital datasignals, calculate relative attributes of source signals from differentsources, etc.

The above methods, instructions, and hardware operate on reference andsuspect signal components. As signals can be represented as a sum ofsignal components formed by projecting the signal onto basis functions,the above methods generally apply to a variety of signal types. TheFourier transform, for example, represents a signal as a sum of thesignal's projections onto a set of basis functions.

The particular combinations of elements and features in theabove-detailed embodiments are exemplary only; the interchanging andsubstitution of these teachings with other teachings in this and theincorporated-by-reference patents/applications are also contemplated.Any headings used in this document are for the reader's convenience andare not intended to limit the disclosure. We expressly contemplatecombining the subject matter under the various headings.

What is claimed is:
 1. A printed object associated with a retail itemcomprising a first layer, the first layer comprising a first area and asecond area, in which the first area and the second area comprisenon-overlapping areas, the first area comprising a first clear coatingprovided thereon, the printed object comprising a non-contiguouscoating, the first clear coating comprising a narrow-band absorptionmaterial with a spectral absorbance peak or maximum in the range of 630nm-710 nm, the first clear coating applied over portions of both thefirst area and the second area in a 2D pattern representing an encodedsignal, the 2D pattern being redundantly applied on the printed object,in which the printed object comprises more area within the first areaand the second area without the first clear coating than area with thefirst clear coating, and in which one or more instances of the 2Dpattern are detectable from machine-analysis of illumination of theprinted package, the illumination have an illumination peak or maximumin the range of 630 nm-710 nm.
 2. The printed object of claim 1 in whichthe first clear coating comprises a varnish or primer printed thereon.3. The printed object of claim 2 in which the second area comprises asecond coating provided thereon with a dry offset printing plate.
 4. Theprinted object of claim 1 in which the absorbance peak or maximumcomprises a peak or maximum between 640 nm-680 nm.
 5. The printed objectof claim 4 in which the absorbance peak or maximum is centered at 660nm, and the illumination peak comprises 660 nm.
 6. The printed object ofclaim 1 in which the absorbance peak comprises a peak or maximum between650 nm-710 nm.
 7. The printed object of claim 6 in which the absorbancepeak or maximum is centered in a range of 668 nm-690 nm, and theillumination peak or maximum is centered in a range of 668 nm-690 nm. 8.The printed object of claim 1 in which the 2D pattern representing anencoded signal represents a digital watermark signal comprising asynchronization component and a variable data component.
 9. The printedobject of claim 8 in which the synchronization component and thevariable data component comprise a merged component.
 10. The printedobject of claim 9 wherein the merged component comprises a thresholdedcomponent, from which some signal from the synchronization component orvariable data component has been removed.
 11. The printed object ofclaim 10 in which the merged component comprises a sparse digitalwatermark signal.
 12. A system comprising: the printed object of claim1, a point of sale scanner comprising an LED with an illumination peakor maximum in the range of 630 nm-710 nm; and a signal detector foranalyzing 2D imagery captured by the point of sale scanner to recoverthe encoded signal.
 13. A method comprising: capturing imagerycorresponding to a printed object with a red illumination scanner, thered illumination scanner having a wavelength at or around 660 nm, saidscanning yielding scan data, wherein the printed object includes a clearcoat printed thereon, the clear coat including a narrow-band absorptionmaterial that has a peak absorbance at or around 660 nm, the clear coatprinted in a manner to convey an encoded plural-bit message, the encodedplural-bit message corresponding to a GTIN number; analyzing the imagerywith one or more programmed multi-core processors to decode the encodedplural bit message, said analyzing yielding the GTIN number; andproviding the GTIN number as an output.
 14. The method of claim 13 inwhich the clear coat comprises a varnish, primer or ink.
 15. The methodof claim 13 in which the encoded plural-bit message is conveyed withdigital watermarking.
 16. The method of claim 13 in which thenarrow-band absorption additive emits fluorescence in the near infraredspectrum.
 17. The method of claim 13 in which the imagery comprisesmonochromatic imagery.
 18. The method of claim 13 in which the clearcoat is printed on a surface of the printed object according to a2-dimensional pattern.
 19. The method of claim 18 in which the2-dimensional pattern comprises a watermark tile pattern.